Commit Graph

473 Commits

  • Python: feat(python): Add MCP client OTel spans per GenAI semantic conventions (#6349)
    * feat(python): Add MCP client OTel spans per GenAI semantic conventions
    
    Implement MCP client spans per the OTel GenAI Semantic Conventions for MCP
    (https://opentelemetry.io/docs/specs/semconv/gen-ai/mcp/#client).
    
    Operations instrumented:
    - initialize: CLIENT span capturing MCP session setup
    - tools/list: CLIENT span for tool listing (per-page)
    - prompts/list: CLIENT span for prompt listing (per-page)
    - tools/call: CLIENT span (nested under execute_tool when called via FunctionTool)
    - prompts/get: CLIENT span
    
    Span attributes follow the MCP semantic conventions:
    - Required: mcp.method.name
    - Conditional: error.type, gen_ai.tool.name, gen_ai.prompt.name
    - Recommended: gen_ai.operation.name, mcp.protocol.version, mcp.session.id,
      network.transport, server.address, server.port
    
    Transport-specific attributes per subclass:
    - MCPStdioTool: network.transport=pipe
    - MCPStreamableHTTPTool: network.transport=tcp, network.protocol.name=http
    - MCPWebsocketTool: network.transport=tcp, network.protocol.name=websocket
    
    All span creation gated behind OBSERVABILITY_SETTINGS.ENABLED.
    
    Closes #3624
    Closes #4697
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor: simplify MCP spans — remove enrichment logic and protocol version caching
    
    - Always create nested CLIENT spans for tools/call instead of enriching
      the parent execute_tool span
    - Remove _ACTIVE_TOOL_EXECUTION_SPAN contextvar (no longer needed)
    - Remove enrich_span_with_mcp_attributes() helper
    - Remove _otel_error_type preservation in FunctionTool.invoke()
    - Remove _mcp_protocol_version instance variable; protocol version is
      only set on the initialize span where it is available
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Refine copilot solution
    
    * fix: enable automatic exception recording on MCP spans
    
    Remove record_exception=False and set_status_on_exception=False from
    create_mcp_client_span. Let OTel handle exception recording and status
    setting automatically. The manual set_mcp_span_error calls for tools/call
    still correctly set error.type (which OTel's automatic handling doesn't
    touch), so tool_error is preserved.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Reduce number of lines
    
    * Add comment to sample
    
    * test: address PR review comments on MCP observability tests
    
    - Fix initialize test to call mocked session.initialize() and read
      protocolVersion from the result instead of hardcoding it
    - Add tools/call McpError error-path test
    - Add prompts/get McpError error-path test
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix export error
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Refactor workflow as agent pending request handling (#6259)
    * WIP: Refactor Workflow as agent pending request handling
    
    * WIP: debugging empty message bug
    
    * Working: Workflow as agent with function approval
    
    * Address Copilot comments
    
    * Fix mypy
    
    * Address comments and fix pipeline
    
    * Request info non function approval now becomes function call
    
    * Revert uv.lock
    
    * Fix mypy
    
    * Bump min version of azure-ai-project
    
    * Remove RequestInfoFunctionArgs
    
    * fix tests
    
    * Fix failing tests
    
    * Fix sample
  • Python: MCP long-running task support in Python (#6319)
    * MCP long-running task support in Python
    
    * Fix pyupgrade and AGENTS.md reconnect description
    
    - pyupgrade: drop forward-reference string annotations in _mcp.py (Python 3.10+ resolves them natively now that MCPTaskOptions is defined before use).
    
    - AGENTS.md: align reconnect description with current behavior. Phase 1 (initial tools/call) does NOT retry on connection loss; raises 'connection lost; task state unknown' instead, so a server that accepted the request but lost the response cannot start the operation twice. Phase 2 (tasks/get / tasks/result) still reconnects once against the same task_id.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix bandit nosec marker for CI pipeline
    
    * Address PR feedbacks
    
    * Clarifiied comments and addressed more PR feedbacks.
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: bump package versions for 1.8.0 release (#6351)
    - Released cohort (core, openai, foundry, root): 1.7.0 -> 1.8.0
    - agent-framework-github-copilot: promote to RC (1.0.0rc1)
    - agent-framework-orchestrations: rc2 -> rc3 (bug fix)
    - Beta/alpha packages with changes: a2a, anthropic, azurefunctions, bedrock,
      foundry-hosting, mistral bumped to new date stamp (260604)
    - Inter-package dependency bounds updated for changed packages
    - CHANGELOG.md and PACKAGE_STATUS.md updated
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Fix compaction message-id collisions and tool-loop summary persistence (#6299)
    * Fix compaction message-id collisions and tool-loop summary persistence
    
    Fixes two bugs in the compaction strategies:
    
    - #5237: incremental group annotation assigned message ids by position
      within the re-annotated slice, so moving the re-annotation start back to
      a previous group start restarted ids at 0 and produced collisions
      (e.g. a user message reusing an assistant message's id), merging groups
      and causing tool-result compaction to wrongly exclude messages.
      group_messages/_ensure_message_ids now take an id_offset and guard
      against existing-id collisions; annotate_message_groups threads the
      slice start index through as the offset.
    
    - #4991: the function-invocation loop copied the message list each
      iteration, so summaries inserted by compaction landed in a throwaway
      copy and were lost across tool-loop iterations (only the persistent
      excluded flags survived). _prepare_messages_for_model_call now compacts
      the list in place when messages is a list, so inserted summaries persist.
    
    Adds regression tests (incremental id uniqueness, existing-id collision
    avoidance, idempotency, and tool-loop summary persistence including
    streaming and conversation-id modes).
    
    Also adds a summarization.py sample demonstrating SummarizationStrategy
    directly with a real client, and reworks advanced.py with tool-call
    groups and a real summarizer.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Guard incremental message-id assignment against prefix-id collisions
    
    Addresses PR review on #5237: _ensure_message_ids only guarded against
    collisions within the re-annotated slice. A preexisting (e.g. user-supplied)
    id in the preserved prefix could still be reassigned in the suffix when the
    id was numerically out of position, merging groups across the re-annotation
    boundary again.
    
    group_messages/_ensure_message_ids now accept reserved_ids, and
    annotate_message_groups passes the preserved prefix's ids so auto-assigned
    suffix ids never collide across the full list. Adds a regression test
    reproducing the out-of-position prefix-id collision.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: run sync tools off the event loop (#5773)
    * fix: run sync tools off event loop
    
    * chore: silence harness tool marker type check
  • Python: Add MCP-based skills discovery (McpSkillsSource) (#6169)
    * Add MCP-based skills discovery (McpSkill, McpSkillsSource, McpSkillResource)
    
    Implement Agent Skills discovery over MCP following the SEP-2640 convention:
    - McpSkillsSource: reads skill://index.json to discover skills served by an MCP server
    - McpSkill: lazily fetches SKILL.md content via resources/read on demand
    - McpSkillResource: wraps MCP resource results (text and binary)
    - Path traversal protection in get_resource for defense in depth
    - Samples for Foundry Toolbox and standalone MCP skills server
    - Comprehensive unit tests (514 lines)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address PR review comments: rename to MCP* convention, fix error handling and samples
    
    - Rename McpSkill/McpSkillResource/McpSkillsSource to MCPSkill/MCPSkillResource/MCPSkillsSource
    - Add data-URI prefix stripping for blob resource decoding
    - Let non-McpError exceptions propagate from get_resource()
    - Fix contradictory test comment
    - Use interactive input() in mcp_based_skill sample
    - Remove misleading sample output block
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Restore debug logging for McpError in get_resource()
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Use AzureCliCredential in Foundry toolbox skills sample for consistency
    
    Replace DefaultAzureCredential with AzureCliCredential to match the
    credential convention used in all other samples.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Use MCPStreamableHTTPTool in MCP skills sample
    
    Replace raw mcp library imports (ClientSession, streamable_http_client)
    with the framework's MCPStreamableHTTPTool to keep MCP server connections
    consistent regardless of whether skills are enabled.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Branch on McpError.error.code so only not-found errors return empty
    
    Previously _try_read_index() and get_resource() swallowed every McpError
    as 'no skills available', making auth failures, server crashes, and
    connection drops indistinguishable from a server that simply has no
    skills.
    
    Now only two codes are treated as not-found:
    - -32002 (MCP-spec Resource not found)
    - -32601 (METHOD_NOT_FOUND — server lacks resources/read)
    
    All other McpError codes and non-McpError exceptions propagate with a
    warning log, surfacing real failures visibly.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Add tests for non-McpError and non-not-found error propagation in MCP skills
    
    Cover the re-raise branch in MCPSkill.get_resource for plain
    ConnectionError/TimeoutError, the generic McpError (code 0) propagation
    on get_resource, and TimeoutError propagation in _try_read_index.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Revert "Use MCPStreamableHTTPTool in MCP skills sample"
    
    This reverts commit f31ed0ded9.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Introduce MCP_SKILLS experimental feature for MCP skill classes
    
    Add a separate MCP_SKILLS feature ID to ExperimentalFeature enum and
    use it for MCPSkillResource, MCPSkill, and MCPSkillsSource, since their
    promotion timeline is partly outside of our control.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: progressive tool exposure via FunctionInvocationContext (#6233)
    * Python: progressive tool exposure via FunctionInvocationContext
    
    Add first-class progressive tool exposure to the Python core function-calling
    loop. Tools can now add or remove real FunctionTool schemas at runtime via the
    injected FunctionInvocationContext, taking effect on the next iteration of the
    loop.
    
    - FunctionInvocationContext gains a live `tools` list plus experimental
      `add_tools()` / `remove_tools()` helpers (feature: PROGRESSIVE_TOOLS).
    - The function-calling loop establishes a run-local, normalized tools list and
      threads it into the context at both invocation paths so mutations propagate.
    - Add a sample (dynamic_tool_exposure.py) and a tools samples README, including
      a note that CodeAct providers (Monty/Hyperlight) use their own provider-level
      tool management instead.
    
    Supersedes #3877.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Validate non-negative input in dynamic_tool_exposure sample tools
    
    Address review feedback: factorial and fibonacci now return an error
    message for negative n instead of producing incorrect results.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Make add_tools atomic and surface swallowed function errors
    
    Address review feedback on progressive tool exposure:
    
    - add_tools now validates the full batch against a throwaway copy before
      committing, so a duplicate-name clash partway through a sequence leaves
      the live tool list unchanged (all-or-nothing).
    - _auto_invoke_function now logs a warning (with traceback) when a tool
      raises, so contract errors such as a duplicate-name ValueError from
      add_tools are debuggable without enabling include_detailed_errors.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Avoid retaining tracebacks when logging swallowed function errors
    
    Logging with exc_info=exc fed the exception traceback to the logging
    machinery, whose frame references created reference cycles collected
    lazily by the cyclic GC. On Windows that could drop a hyperlight
    WasmSandbox on a non-owning thread ("unsendable, dropped on another
    thread"), crashing the xdist worker. Log a pre-formatted message with
    the exception repr instead, so no traceback object is retained.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * added missing decorator
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Promote agent-framework-declarative package to RC (#6256)
    * Promote agent-framework-declarative package to RC
    
    * Update missed package status file.
  • Python: Fix OTLP HTTP base-endpoint losing /v1/{signal} auto-append (#5913)
    * Python: Fix OTLP HTTP base-endpoint losing /v1/{signal} auto-append
    
    Per the OTel spec, OTEL_EXPORTER_OTLP_ENDPOINT is a *base* URL for HTTP —
    the SDK auto-appends /v1/traces, /v1/metrics, /v1/logs when it reads the
    env var directly. Signal-specific endpoint env vars are *full* URLs used
    verbatim.
    
    _get_exporters_from_env read the base endpoint and forwarded it as the
    constructor ``endpoint=`` argument, which the SDK always treats as a full
    signal URL. As a result, with OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
    and HTTP protocol, the exporter sent to http://localhost:4318 instead of
    http://localhost:4318/v1/traces (and likewise for metrics/logs).
    
    Replicate the spec's auto-append here when falling back to the base
    endpoint under HTTP. gRPC behavior is unchanged.
    
    * Python: Fix mypy type errors in OTLP endpoint assignment
    
    Pre-declare traces_endpoint, metrics_endpoint, logs_endpoint as
    str | None before the if/else block. Mypy inferred str from the
    if-branch f-string assignments and then rejected the str | None
    expressions in the else-branch as incompatible.
  • Python: feat(evals): Foundry Adaptive Evals integration (rubric-generation) (#6101)
    * Python: feat(evals): RubricScore type + EvalScoreResult.dimensions
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(foundry-evals): RubricDimension + GeneratedEvaluatorRef + accept in evaluators=
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(evals): parse rubric_scores from output items + assertion helpers
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(evals): BaseAgent.as_eval_source / Workflow.as_eval_source
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(foundry-evals): EvalGenerationSource + generate_rubric helper
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(foundry-evals): YAML config loader + sample
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: fix(evals): address PR review feedback
    
    Addresses 4 Copilot review comments on PR #6101:
    
    1. assert_dimension_score_at_least: drop the (not evaluator or found_any) guard so require_applicable=True correctly raises when the named evaluator produces no entries for the dimension. Adds TestRubricAssertions covering the regression.
    
    2. GeneratedEvaluatorRef docstring: reword to describe actual behaviour (pinning recommended, not required) so it matches the dataclass default and FoundryEvals warning path.
    
    3. _poll_generation_job: switch from asyncio.get_event_loop() to get_running_loop() and bound the per-iteration sleep by remaining time, matching _poll_eval_run.
    
    4. generate_rubric: type category as Literal['quality','safety'] and validate at the entry point with a ValueError; drop the silent 'invalid -> quality' rewrite in _generation_job_to_ref. Adds a regression test.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: feat(foundry-evals): hosted-agent-aware rubric generation
    
    * Auto-detect hosted Foundry agents in agent_as_eval_source: when the
      agent's chat_client exposes a string agent_name (the convention used
      by RawFoundryAgentChatClient for PromptAgents/HostedAgents), emit a
      type='agent' EvalGenerationSource so the service fetches instructions
      and tools from the agent registry instead of relying on the local
      wrapper (which holds neither for hosted agents).
    * Add hosted_agent_version kwarg and a new agent_version field on
      EvalGenerationSource so PromptAgent runs can pin to a specific hosted
      version for reproducible rubric generation.
    * Add force_prompt_source escape hatch to bypass auto-detection and
      always emit a rendered prompt dossier - useful when the local wrapper
      carries overrides the service-side agent doesnt see.
    * Fix _to_sdk_source for dataset sources: SDK ctor takes name=/version=,
      not dataset_name=/dataset_version=. The mismatch would raise TypeError
      against the real azure-ai-projects 2.3.0a* SDK; only unmocked
      integration paths were affected.
    
    Tests cover: auto-detection happy path, versionless hosted agent,
    explicit hosted_agent_version forwarding, force_prompt_source override,
    non-string chat_client attrs (MagicMock test doubles) not mis-detected,
    agent_version forwarded through _to_sdk_source, and the corrected
    dataset SDK kwarg names.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry-evals): accept canonical dimension_scores key per docs
    
    The published Foundry rubric-evaluator output (Microsoft Learn 'Rubric evaluators' reference) places per-dimension breakdowns under properties.dimension_scores, not properties.rubric_scores. The parser now tries dimension_scores first and falls back to rubric_scores for preview-build compatibility, and tolerates non-list payloads (e.g. MagicMock auto-attrs) by trying the next candidate when parsing yields zero entries.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * feat(foundry-evals): add manual create_rubric_evaluator
    
    Adds FoundryEvals.create_rubric_evaluator as the agent-framework surface over project_client.beta.evaluators.create_version. This is the manual counterpart to generate_rubric: callers supply RubricDimension instances (authored locally, ported from another framework, or hand-tuned) and we POST a RubricBasedEvaluatorDefinition. The service auto-attaches the non-editable residual dimension (general_quality for quality, general_policy_compliance for safety).
    
    Per the Microsoft Learn 'Rubric evaluators' reference, the auto-generation path (create_generation_job) is primarily a portal/UI feature; external SDK clients with rich local agent context are better served by manual create_version. This keeps generate_rubric for users who want to round-trip through a Foundry-registered agent.
    
    Validation up front: weight must be in [1,10], ids unique, descriptions non-empty, pass_threshold in [0,1]. The returned GeneratedEvaluatorRef is identical in shape to one obtained from generate_rubric, so downstream evaluators= lists work unchanged.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * samples(foundry-evals): manual rubric sample + namespace re-exports
    
    Adds evaluate_with_manual_rubric_sample.py demonstrating the end-to-end dev scenario for FoundryEvals.create_rubric_evaluator: hand-author a list of RubricDimension, register via create_rubric_evaluator, then use the pinned GeneratedEvaluatorRef alongside built-in evaluators in an agent regression run.
    
    Also re-exports RubricDimension, GeneratedEvaluatorRef, build_sources, and load_evals_config from agent_framework.foundry (both the lazy runtime shim and the type stub) so the rubric samples can import everything from a single namespace; the auto-generate sample was previously broken because the shim was missing build_sources / load_evals_config.
    
    Updates the foundry-evals README with a chooser entry for the two rubric paths.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * feat(foundry-evals): remove rubric creation flows; keep consumption only
    
    Reframes agent-framework as a pure consumer of Foundry rubric evaluators: scoring against rubrics that already exist (authored in the Foundry portal or via the dedicated SDK / REST surface) instead of creating them from the SDK.
    
    Removed creation surface area:
    
    - FoundryEvals.generate_rubric (auto-generate path) and create_rubric_evaluator (manual path), plus all _GenerationSdkTypes / _ManualRubricSdkTypes / _to_sdk_dimensions / _coalesce_generation_sources / _to_sdk_source / _poll_generation_job / _generation_job_to_ref / _evaluator_version_to_ref / _get_beta_evaluators / _import_*_sdk_types helpers.
    
    - EvalGenerationSource (the input source discriminator), RubricDimension (the input dimension type), agent_as_eval_source / workflow_as_eval_source / _detect_hosted_foundry_agent helpers, and the YAML-config loader (_evals_config.py with RubricGenerationSpec / RubricSourceSpec / parse_evals_config / load_evals_config / build_sources).
    
    - BaseAgent.as_eval_source / Workflow.as_eval_source plus the _render_agent_dossier / _render_workflow_dossier helpers in core. These existed only to feed the now-removed generation pipeline.
    
    - Samples evaluate_with_generated_rubric_sample.py, evaluate_with_manual_rubric_sample.py, and evaluators.yaml. Replaced with a short README section showing how to reference an existing rubric evaluator via GeneratedEvaluatorRef.
    
    Kept (consumption surface):
    
    - GeneratedEvaluatorRef, slimmed to (name, version, display_name). Still accepted alongside built-in evaluator strings in FoundryEvals(evaluators=[...]). Versionless refs still warn.
    
    - RubricScore on EvalScoreResult.dimensions plus EvalResults.assert_dimension_score_at_least for per-dimension CI gates.
    
    - _parse_dimension_entries / _extract_rubric_scores output parsing (both canonical dimension_scores and the legacy rubric_scores key).
    
    Tests: 160/160 foundry unit tests and 71/71 core local-eval tests pass; pyright is clean across changed files. The pre-existing tests/core/test_telemetry.py::test_detect_hosted_fallback_import_error failure is unrelated and reproduces on the prior commit.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * samples(foundry-evals): add evaluate_with_rubric_sample
    
    Adds a runnable end-to-end sample showing how to consume a pre-existing rubric evaluator created in Foundry: reference it with GeneratedEvaluatorRef(name, version), mix it with built-in evaluators in FoundryEvals, and gate CI with assert_dimension_score_at_least on a specific dimension.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry-evals): satisfy mypy on _fetch_output_items
    
    mypy infers OutputItemListResponse.sample as dict[str, object] | None while pyright correctly infers the typed Sample model. Cast to Any so both type checkers accept the attribute access pattern, rename the local to avoid shadowing the inner-loop sample binding, and drop the now-stale pyright suppressions.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(foundry-evals): drop unpublished rubric-evaluators learn.microsoft.com link
    
    The Adaptive Evals authoring docs are not yet published on Microsoft Learn, so the link 404s. Keep the descriptive text without the broken hyperlink; we can re-add it once the docs ship.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * test(foundry-evals): hoist repeated local imports to module top
    
    Per code review feedback (eavanvalkenburg): the test file repeated 'from agent_framework_foundry._foundry_evals import ...' inside 22 test bodies and 'from agent_framework_foundry import GeneratedEvaluatorRef' inside 8 more. Move all of them to the existing top-level imports; the symbols are the same across tests and the local imports were redundant.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Fix core observability unsafe serialization of function-call arguments containing dataclass/framework objects (#6026)
    * fix: safely serialize function-call arguments in core observability
    
    Apply make_json_safe() to content.arguments in _to_otel_part() before
    building the otel message dict, so that dataclass/framework payloads
    (e.g. workflow request_info events) do not cause a TypeError when
    _capture_messages() calls json.dumps().
    
    Lift make_json_safe() into agent_framework._serialization (no new
    external deps — dataclasses/datetime only) so the core observability
    path can use it without a dependency on the ag-ui adapter.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(core): safely serialize workflow request_info payloads in observability (#5733)
    
    - Add make_json_safe() helper to recursively convert non-serializable objects
    - Use make_json_safe() in _to_otel_part() for function_call arguments
    - Fix CustomPayload test class to use @dataclass (resolves B903 lint error)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(serialization): guard callability and normalize dict keys in make_json_safe (#5733)
    
    - Use callable(getattr(obj, method, None)) instead of hasattr() so that
      non-callable attributes named model_dump/to_dict/dict do not raise
      TypeError at runtime.
    - Wrap each call in try/except TypeError to handle callables with
      mandatory arguments gracefully.
    - Convert dict keys to str() so that non-string keys (e.g. datetime,
      int) cannot cause json.dumps to raise TypeError.
    - Add regression tests for both scenarios.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address observability serialization review feedback
    
    ---------
    
    Co-authored-by: Copilot <copilot@github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: refresh dev dependencies and validate runtime bounds (#6238)
    Updates third-party dev dependencies across the Python workspace and
    validates that all runtime dependency bounds still hold at both ends.
    
    Dev dependency bumps (root, lab, declarative, durabletask):
    - uv 0.11.6 -> 0.11.17, ruff 0.15.8 -> 0.15.15,
      pytest-asyncio 1.3.0 -> 1.4.0, mcp 1.27.0 -> 1.27.2,
      azure-monitor-opentelemetry 1.8.7 -> 1.8.8,
      poethepoet 0.42.1 -> 0.46.0, prek 0.3.9 -> 0.4.3,
      types-python-dateutil and types-PyYaml stub bumps.
    - Transitive Dependabot items swept via lock: idna 3.11 -> 3.17,
      pip 26.0.1 -> 26.1.2.
    
    Deliberately excluded:
    - opentelemetry-sdk stays 1.40.0: azure-monitor-opentelemetry (incl.
      1.8.8) hard-pins opentelemetry-sdk==1.40.
    - mypy stays 1.20.0 and pyright stays 1.1.408: the 2.1.0 / 1.1.409
      bumps introduce new diagnostics that fail type checking and need
      dedicated PRs.
    - rich kept as a range: agentlightning (lab[lightning]) forces
      rich==13.9.4.
    
    Code/formatting changes driven by the ruff upgrade:
    - devui lifespan now uses try/finally so shutdown cleanup always runs
      (ruff RUF075).
    - Removed unused TYPE_CHECKING imports in core and foundry flagged by
      ruff 0.15.15.
    - Reapplied ruff 0.15.15 formatting to the files it changed.
    
    Validation: validate-dependency-bounds-test "*" passes (31/31 lower +
    31/31 upper); typing 62/62; lint 31/31; devui tests pass.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Add background agent support to harness agent (#6155)
    * Add background agent support to harness agent
    
    * Address PR comments
  • Python: coalesce code interpreter history chunks (#5801)
    * fix: coalesce code interpreter history chunks
    
    * fix: narrow content item list types
    
    * fix: remove redundant content list casts
  • Python: consolidate MCP reliability fixes (#6145)
    * Python: consolidate MCP reliability fixes
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix MCP cleanup and metadata typing
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Satisfy MCP metadata mypy typing
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix Pyright metadata mapping type
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Adding AgentFileStore and FileAccessProvider to support file access operations. (#6099)
    * Adding AgentFileStore and FileAccessProvider to support file ased operations for agents.
    
    * Address PR review feedback on FileAccessProvider
    
    - Probe symlinks on the unresolved candidate path so in-root symlinks
      cannot silently pass and out-of-root symlinks surface the correct
      error message.
    - Validate matching_lines elements in FileSearchResult.from_dict and
      raise a clean ValueError for non-mapping entries.
    - Cap search regex pattern length (256 chars) via a new
      _compile_search_regex helper to mitigate ReDoS, and surface the cap
      in the file_access_search_files tool description.
    - Skip non-UTF-8 files during filesystem search instead of aborting
      the entire directory walk.
    - Replace the module-scope trailing string in the data-processing
      sample with comments to avoid Ruff B018.
    - Remove the checked-in working/region_totals.md sample artifact so
      the save flow works from a clean checkout.
    - Expand the Windows stdout reconfiguration comment in task_runner.py
      for clarity.
    - Add tests for invalid/oversize regex, non-UTF-8 file search, and
      in-root symlink rejection.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix mypy redundant-cast in FileSearchResult.from_dict
    
    Use cast(list[object], ...) instead of cast(list[Any], ...) so the
    cast represents a real type change (lists are invariant) and is no
    longer flagged by mypy as redundant, while still satisfying pyright's
    reportUnknownVariableType. Matches the existing pattern in _memory.py.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Tighten path normalization and directory resolution in FileAccess
    
    - _normalize_relative_path now strips surrounding whitespace up front
      so leading/trailing spaces never leak into file segments, and
      rejects trailing path separators for file paths so 'foo/' is no
      longer silently coerced to 'foo'.
    - FileSystemAgentFileStore._resolve_safe_directory_path normalizes
      with is_directory=True and maps an empty normalized result to the
      root. This matches InMemoryAgentFileStore so whitespace-only
      directory inputs resolve to the root instead of raising.
    - Added tests for whitespace stripping, trailing-separator rejection,
      and whitespace-only directory listing on the filesystem store.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Harden FileAccess search and atomic save in store API
    
    - Add wall-clock timeout (10s) around regex scans so a pathological pattern (e.g. `(a+)+`) below the length cap cannot stall the event loop.
    - Offload the InMemoryAgentFileStore regex scan to a worker thread, matching the filesystem store.
    - Fail closed when `Path.is_symlink` raises during the safe-path probe so a permission error cannot silently bypass the symlink/reparse-point rejection.
    - Add `overwrite: bool = True` to `AgentFileStore.write_file`; the in-memory store performs the check under the existing lock and the filesystem store uses `open(mode='x')` so concurrent callers cannot race past `overwrite=False`.
    - `file_access_save_file` now relies on the atomic store call instead of a separate `file_exists` round-trip.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix Python 3.10 timeout handling and add directory arg to list/search tools
    
    - Catch asyncio.TimeoutError in _run_search_with_timeout. In Python 3.10
      asyncio.wait_for raises asyncio.exceptions.TimeoutError, which is
      distinct from the builtin TimeoutError (the two were unified in 3.11).
      Catching the asyncio alias works on every supported version.
    - Add an optional directory parameter to file_access_list_files and
      file_access_search_files so agents can enumerate / scope searches to
      nested folders, not just the store root.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address FileAccess review feedback: case, errors, signal, TOCTOU
    
    - InMemoryAgentFileStore now stores (display_name, content) so list_files
      and search_files return the original-case names callers wrote, matching
      the behaviour of FileSystemAgentFileStore on case-preserving filesystems
      and removing the silent in-memory vs. on-disk contract divergence.
    - FileSystemAgentFileStore.read_file raises ValueError instead of letting
      UnicodeDecodeError bubble for binary / non-UTF-8 input, restoring
      symmetry with search_files (which still skips) and giving the tool
      layer a recoverable type to translate.
    - Tool wrappers now catch ValueError and OSError around every operation
      and surface them as readable strings, so 'you used ..' and 'the file
      already exists' are both reported to the model the same way instead of
      the former crashing out as an unhandled exception.
    - _search_files_sync logs per skipped non-UTF-8 file at WARNING and an
      aggregate INFO summary so operators can distinguish 'no matches' from
      'half the corpus was unreadable'.
    - FileSystemAgentFileStore softens its docstrings to acknowledge the
      inherent probe-then-open TOCTOU window. On POSIX both read and write
      now pass O_NOFOLLOW so the kernel refuses if the leaf segment becomes
      a symlink between the probe and the open. Windows has no equivalent
      flag; the limitation is documented.
    - Tests cover: case preservation on list/search, ValueError on non-UTF-8
      read at the store and tool layer, tool-layer string responses for
      path-traversal and oversized-regex inputs, search-skip log output,
      symlink rejection on delete/search/list, and symlinked intermediate
      directory rejection.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address FileAccess nit comments: docstrings, enumerate, opt-in delete approval
    
    - Expand FileSearchMatch/FileSearchResult.to_dict docstrings to explain why
      the override is needed (__slots__ defeats the mixin's __dict__ iteration)
      and why exclude/exclude_none are accepted-but-ignored (mixin signature
      compatibility for callers like to_json).
    - Use enumerate(lines, start=1) in _search_file_content so the +1 below is
      no longer needed; rename loop variable to line_number for clarity.
    - Add opt-in require_delete_approval: bool = False on FileAccessProvider.
      When True, file_access_delete_file is registered with approval_mode
      'always_require' so the host must approve every delete. Default False
      preserves current behaviour and matches the .NET reference, but
      deployments that want a safer-by-default posture can enable it.
    - Add tests covering both delete approval modes.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * FileAccess: require delete approval by default
    
    Flip the default for FileAccessProvider(require_delete_approval=...) from
    False to True so destructive deletes are gated by host approval out of the
    box. Callers that want the previous autonomous behaviour (which matches the
    .NET reference) can pass require_delete_approval=False.
    
    Tests updated accordingly.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fixing linkinspector by installing Chrome for puppeteer first.
    
    ---------
    
    Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: [Breaking] Refactor Skill API to async resource and script lookup (#6135)
    Port of .NET commit 08541ee5a9.
    
    Replace property-based Skill.content/resources/scripts with async
    by-name lookup methods:
    - content property -> async get_content() -> str
    - resources property -> async get_resource(name) -> SkillResource | None
    - scripts property -> async get_script(name) -> SkillScript | None
    
    SkillsProvider now always includes all three tools (load_skill,
    read_skill_resource, run_skill_script) and both instruction blocks
    regardless of whether any skills have resources or scripts.
    
    ClassSkill retains resources/scripts properties as overridable hooks
    for subclass reflection-based discovery.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Bump Python package versions for 1.7.0 release (#6142)
    Bumps the released 1.6.0 packages agent-framework, agent-framework-core, agent-framework-foundry, and agent-framework-openai to 1.7.0, with root continuing to exactly pin agent-framework-core[all]. Bumps the changed prerelease packages agent-framework-a2a, agent-framework-chatkit, agent-framework-declarative, agent-framework-devui, and agent-framework-foundry-hosting to the 260528 date stamp, raises core floors on the packages included in this release, raises Foundry's OpenAI floor alongside OpenAI, and raises ChatKit's openai-chatkit floor to the minimum version required by the current typed API usage. No beta cohort bump was applied; the absent mistal/mistral package was intentionally not bumped because no such package exists in this branch.
  • Python: Align c# and python TodoProvider tool names (#6107)
    * Align c# and python TodoProvider tool names
    
    * Potential fix for pull request finding
    
    Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
    
    * Address PR review: remove __slots__ and add typed schemas for tool params
    
    - Remove __slots__ from TodoItem, TodoInput, and TodoCompleteInput classes
      (not needed for low-instance-count objects and hinders dev scenarios)
    - Add _TodoAddItemSchema and _TodoCompleteItemSchema TypedDicts to provide
      proper JSON schema for todos_add and todos_complete tool parameters
    - Use typing_extensions for Python 3.10 compatibility
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • feat(a2a): add A2AAgentSession with reference_task_ids and input-required support (#5980)
    * feat(a2a): link follow-up messages via reference_task_ids
    
    Track the task_id from A2A responses (task, status_update, artifact_update,
    and message payloads) on session.state and include it as reference_task_ids
    on subsequent outgoing messages. This enables remote agents to correlate
    follow-up messages as task refinements per the A2A spec.
    
    Resolves #5938
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * feat(a2a): add A2AAgentSession for typed protocol state tracking
    
    Introduce A2AAgentSession (subclass of AgentSession) with context_id,
    task_id, and task_state properties. This follows the DurableAgentSession
    pattern and mirrors the .NET A2AAgentSession design.
    
    - Track task_id, context_id, and task_state from all response payload types
    - Validate context_id consistency (raise on mismatch)
    - Auto-assign server-generated context_id when not set
    - Only A2AAgentSession gets reference tracking (no state dict fallback)
    - Plain AgentSession continues to work without reference tracking
    - Add serialization support (to_dict/from_dict)
    - Export via agent_framework.a2a and agent_framework_a2a
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * style: remove unnecessary string annotation (pyupgrade)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: use AgentSession.from_dict for state deserialization
    
    Avoids importing private _deserialize_state, matching the
    DurableAgentSession pattern.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: track context_id from message payloads in A2AAgentSession
    
    Previously, context_id was only captured from task, status_update, and
    artifact_update payloads. Message-only responses (which carry context_id
    but may lack task_id) were silently lost. This fix:
    
    - Captures msg.context_id in the message handler
    - Persists session state when either last_task_id or last_context_id is
      present (not only when task_id is truthy)
    - Only updates task_id/task_state when a task_id was actually returned
    - Adds a test for message-only context_id tracking
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * addressed comments
    
    * Gate status content to INPUT_REQUIRED/terminal states (match .NET)
    
    Match .NET's GetUserInputRequests pattern: only emit TaskStatusUpdateEvent
    message content when state is INPUT_REQUIRED or terminal. Intermediate
    status text (WORKING, SUBMITTED) is no longer surfaced to callers.
    
    When state is INPUT_REQUIRED, set additional_properties['input_required']
    = True so callers can distinguish input requests from final responses.
    
    Closes #5937
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review: remove message task_id tracking, defensive fallbacks, and input_required flag
    
    - Do not track task_id from Message payloads (simple interactions
      without task tracking)
    - Remove 'or last_task_id' fallback from status_update and
      artifact_update handlers (spec guarantees task_id is always set)
    - Remove additional_properties['input_required'] flag (content gating
      to INPUT_REQUIRED/terminal states is the signal itself)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Add a HarnessAgent with available features and sample (#6041)
    * Add a HarnessAgent with available features and sample
    
    * Fix formatting
    
    * Address PR comments and fix mypy error
    
    * Add web search support to HarnessAgent
    
    * Fix build warning
    
    * Apply suggestions from code review
    
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
    
    * Address PR comments
    
    * Address PR comments
    
    * Address further PR comments.
    
    * Fix markdown broken link
    
    ---------
    
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
  • Python: feat(foundry): add to_prompt_agent / deploy_as_prompt_agent (experimental) (#5959)
    * feat(foundry): add experimental to_prompt_agent converter
    
    Adds `to_prompt_agent(agent)`, an experimental converter
    (`ExperimentalFeature.TO_PROMPT_AGENT`) that turns an Agent Framework
    `Agent` into a Foundry `PromptAgentDefinition` ready to publish via
    `AIProjectClient.agents.create_version(...)`.
    
    Behaviour:
    
    * `agent.client` must be a `FoundryChatClient` (or subclass); otherwise
      `TypeError` is raised. The model deployment name is lifted from the
      bound client so the same Agent definition used for local runs can be
      published as a hosted prompt agent without restating the model.
    * Foundry SDK tool instances (from `FoundryChatClient.get_*_tool()`) are
      passed through unchanged. AF `FunctionTool`s (and `@tool`-decorated
      callables) are emitted as Foundry `FunctionTool` declarations.
    * Local AF MCP tools cannot be expressed in a `PromptAgentDefinition`;
      the converter raises `ValueError` and points at
      `FoundryChatClient.get_mcp_tool()` for hosted MCP servers.
    * The converter walks both `agent.default_options["tools"]` and
      `agent.mcp_tools` because `normalize_tools()` splits local MCP off
      into its own list.
    
    Re-exported through the `agent_framework.foundry` lazy-loading namespace
    (updates both `__init__.py` and the `__init__.pyi` type stub).
    
    Adds a portable-agent sample showing the same `Agent` driven through
    both `agent.run(...)` and `to_prompt_agent(agent)`, and a README section
    covering the new converter.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * chore(samples): remove snippet tags from portable agent sample
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * chore(samples): inline FoundryChatClient and enable prompt-agent publish
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * chore(samples): drop async credential context manager
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(foundry): trim README to_prompt_agent example to publish-only flow
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(foundry): note FoundryAgent runs @tool callables for deployed prompt agents
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): address review comments on to_prompt_agent converter
    
    * Construct `PromptAgentDefinition` `Tool` from a dict via `**tool_item`
      unpacking rather than the positional Mapping constructor \u2014 cleaner and
      matches the typical Pydantic / Azure SDK pattern.
    * Drop the redundant `isinstance(mcp_tool, MCPTool)` guard in
      `_convert_tools`; the parameter is already typed `Iterable[MCPTool]` so
      the second `raise` was unreachable. The remaining single `raise`
      fires for every entry as intended.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): match Agent.__init__ model resolution in to_prompt_agent
    
    * Read the model from `agent.default_options.get("model")` first,
      falling back to `agent.client.model`. This mirrors the order
      `Agent.__init__` uses (`_agents.py:740`) when assembling
      default_options, so the model the agent runs with is the same model
      the converter publishes \u2014 e.g. when the caller passes
      `default_options={"model": "..."}` to override the bound client.
    * Updated the missing-model error message to point at both the client
      and the default_options paths.
    * Added tests:
      * tool-only agent with no `instructions` produces a definition
        where `instructions` is `None` and is omitted from the dict
        payload (`Agent.__init__` strips None values from default_options
        before storing them).
      * `default_options['model']` wins over the bound client's model.
      * Fallback to client.model when default_options has no model.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * feat(foundry): add deploy_as_prompt_agent helper + samples
    
    Adds `deploy_as_prompt_agent(agent)`, a convenience wrapper around
    `to_prompt_agent` that reuses the bound FoundryChatClient's project
    client to call `project_client.agents.create_version(...)`. Defaults
    `agent_name` / `description` from `agent.name` / `agent.description`
    so the Agent stays the single source of truth.
    
    * Exposed from `agent_framework_foundry` and the lazy-loading
      `agent_framework.foundry` namespace (including the .pyi stub).
    * Marked experimental with the existing
      `ExperimentalFeature.TO_PROMPT_AGENT` tag.
    * Tests cover the happy path, name/description defaulting, explicit
      override, no-name error, metadata + description forwarding, extra
      kwargs passthrough, and the experimental metadata.
    
    Samples:
    * Renamed the existing sample to `creating_prompt_agents.py`, drops
      'portable' wording, presents `deploy_as_prompt_agent` first as the
      recommended path and `to_prompt_agent` + `AIProjectClient` as the
      two-step alternative, and adds a cleanup step that deletes the
      published agent so re-runs stay idempotent.
    * New `using_prompt_agents.py` shows the end-to-end loop: deploy the
      agent, connect to it with `FoundryAgent` passing the same local
      `@tool` callable, run a query against the deployed prompt agent,
      then clean up.
    
    README updated to introduce `deploy_as_prompt_agent` as the
    recommended path and link to both runnable samples.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): restore missing-model ValueError in to_prompt_agent
    
    The check was accidentally dropped while reworking docstrings in the
    previous commit. Test `test_to_prompt_agent_rejects_missing_model`
    exercises this path and was failing on CI as a result.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor(foundry): rename deploy_as_prompt_agent -> create_prompt_agent
    
    Renames the helper across the foundry package, core lazy-loader stubs,
    tests, README and samples. The new name better matches the action
    performed (a prompt-agent definition is created in Foundry) and is
    consistent with the surrounding ''create_*'' API surface.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor(foundry): drop create_prompt_agent, enrich to_prompt_agent params
    
    Remove the create_prompt_agent helper and consolidate on to_prompt_agent.
    Expose every PromptAgentDefinition parameter that has either an Agent
    Framework equivalent (sourced from default_options) or no equivalent
    (accepted as a keyword argument).
    
    * default_options-sourced (with kwarg overrides):
      temperature, top_p, string tool_choice
    * kwarg-only Foundry knobs:
      reasoning, text, structured_inputs, rai_config, ToolChoiceParam tool_choice
    
    Precedence is always: explicit keyword > default_options entry > unset.
    
    Tests cover every path (defaults, default_options, kwargs, kwarg override).
    Samples and README rewritten around the enriched to_prompt_agent.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor(foundry): single source of truth for prompt-agent options
    
    Stop duplicating the generation-parameter surface between FoundryChatOptions
    and to_prompt_agent. Translate every field with an Agent Framework equivalent
    (temperature, top_p, tool_choice, reasoning, response_format/text/verbosity)
    from agent.default_options via a new RawFoundryChatClient helper
    _prepare_prompt_agent_options. Only Foundry-specific fields with no AF
    equivalent — structured_inputs and rai_config — remain as keyword arguments
    on to_prompt_agent.
    
    - tool_choice is dropped when there are no tools (mirrors _prepare_options
      semantics and avoids polluting tool-less prompt agents with Agent.__init__'s
      'auto' default).
    - response_format Pydantic models route through
      openai.lib._parsing._responses.type_to_text_format_param; dict shapes go
      through the existing _prepare_response_and_text_format helper.
    - default_options is not mutated; text dict is defensively copied.
    
    Tests, README, and creating_prompt_agents.py sample updated to reflect the
    new single-source model.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(foundry): consolidate prompt-agent sample
    
    Drop creating_prompt_agents.py (the publish-only variant) and rename
    using_prompt_agents.py to foundry_prompt_agents.py so the single sample
    covers the full convert -> publish -> connect -> run loop. Update the
    README link list accordingly.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(foundry): run local Agent + deployed agent in same sample
    
    Add an agent.run() call against the local Agent before publishing, then run
    the deployed prompt agent on the same query. Expand the docstring with a
    compare-and-contrast covering runtime/latency, configurability, and
    persistence/sharing differences between the two execution paths.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * test(foundry): cover conflicting response_format + text.format in to_prompt_agent
    
    Exercises the ValueError path when a Pydantic response_format would overwrite
    an explicit text.format mapping with a different shape. Lifts _chat_client.py
    coverage from 89% to 90%.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor(foundry): move _prepare_prompt_agent_options into _to_prompt_agent
    
    Lift the translation helper off RawFoundryChatClient and into the
    _to_prompt_agent module as a module-private function that takes the client
    as its first argument. The chat client no longer needs to carry a method
    whose only consumer is the prompt-agent converter, while still serving as
    the source of the request-path helper (_prepare_response_and_text_format)
    that the converter reuses for dict-shaped response_format values.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs(python): codify GA terminology + post-run docs review
    
    Add two pieces of guidance to python/AGENTS.md:
    
    * Terminology - reserve 'GA' for hosted services; use 'released' or 'stable'
      for Agent Framework code/features to match the feature-lifecycle stages.
    * Maintaining Documentation - review AGENTS.md and skills at the end of every
      run and update any guidance the conversation made stale; before adding a
      new principle, ask the user to confirm it should be captured.
    
    Also pulls in a docstring fix in foundry_prompt_agents.py that swaps the
    stray 'GA' for 'released', applying the new terminology rule.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * address PR review: strict=True default, Tool._deserialize dispatch, sample cleanup safety
    
    - FunctionTool published as strict=True so the server-side schema validation
      matches what the local FoundryAgent(tools=[same_callable]) dispatcher
      enforces. AF FunctionTool has no 'strict' attribute, so the safer default
      is used uniformly instead of silently downgrading to a permissive contract.
    - _validate_mapping_tool now dispatches through ProjectsTool._deserialize so
      dict-shaped tools rehydrate to the concrete subclass (FunctionTool,
      WebSearchTool, ...) via the 'type' discriminator instead of returning a
      generic Tool. Added a test that asserts isinstance(WebSearchTool) and a
      new test for the function-typed dict path.
    - foundry_prompt_agents.py sample now wraps credential + project client in
      async with and the create_version / run flow in try/finally so a failure
      on connect or run still deletes the published prompt agent rather than
      leaving an orphaned, billable resource in the user's Foundry project.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(ci): correct linkspector ignorePattern typo (./pulls -> ./pull)
    
    GitHub PR URLs use the singular segment /pull/N (compare to /issues/N
    for issues). The existing './pulls' ignore pattern never matched
    anything as a result, so legitimately stale PR links (e.g. PRs deleted
    from forks) surface as linkspector failures on unrelated PRs.
    
    This is the same convention the './issues' rule above already follows.
    Fixes the markdown-link-check failure on a dangling link in
    dotnet/src/Microsoft.Agents.AI.DurableTask/CHANGELOG.md.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Add a BackgroundAgentsProvider for python (#6069)
    * Add a BackgroundAgentsProvider for python
    
    * Address PR comments and fix linting warnings
    
    * Address PR comment
  • Python: Align ModeProvider tool names and instructions (#6071)
    * Align ModeProvider tool names and instructions
    
    * Address PR comments
  • Python: fix(core): point @experimental warnings at user code, not stdlib internals (#5996)
    * fix(core): point @experimental warnings at user code, not stdlib internals
    
    Previously the wrappers installed by @experimental called warnings.warn
    with a fixed stacklevel=3. ABCMeta inserts an extra abc.__new__ frame
    when an experimental ABC is subclassed, so the warning landed inside
    abc.py (or <frozen abc>:106 on modern CPython) instead of the user's
    class Sub(...) line.
    
    Resolve the user frame by walking inspect.currentframe(), skipping
    frames whose module name is abc/functools/typing/contextlib (or
    submodules), then emit via warnings.warn_explicit so the recorded
    filename/lineno point at user code. Falls back to warnings.warn with
    stacklevel=2 if no user frame is found. Module-name matching is used
    because frozen stdlib modules report '<frozen abc>' as their filename.
    
    Also install a one-line warnings.formatwarning specifically for
    FeatureStageWarning so 'file:line: ExperimentalWarning: [ID] Name ...'
    prints without the secondary source-snippet line. Other categories
    delegate to the stdlib default formatter unchanged.
    
    Added a regression test that subclasses an @experimental ABC inside
    warnings.catch_warnings and asserts the recorded filename equals the
    test file.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(core): address review feedback on @experimental warning fix
    
    - Make _install_feature_stage_formatter idempotent: tag the installed
      formatter with a marker attribute and short-circuit re-installation,
      so re-imports/reloads don't wrap the formatter on top of itself.
      Also expose the previous formatter via __wrapped__ for restoration.
    - Avoid leaking frame references in _resolve_user_frame: capture data
      into plain locals inside try and del frame/candidate in finally,
      per CPython's guidance on inspect.currentframe usage.
    - Drop redundant _WARNED_FEATURES.clear() in the new ABC subclass test
      (the autouse fixture already handles it).
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * changed query for foundry web search test
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: bump package versions for 1.6.0 release (#6017)
    * Python: bump package versions for 1.6.0 release
    
    - Released cohort (agent-framework, core, openai, foundry): 1.5.0 -> 1.6.0
    - Beta packages (21 packages): 1.0.0b260519 -> 1.0.0b260521
    - Alpha packages (azure-contentunderstanding, foundry-hosting, gemini, monty): 1.0.0a260518/19 -> 1.0.0a260521
    - ag-ui stays at 1.0.0rc2, orchestrations at 1.0.0rc1 (dependency bounds updated)
    - Inter-package dependency lower bounds updated (>=1.5.0,<2 -> >=1.6.0,<2)
    - Update CHANGELOG compare links
    - uv.lock refreshed
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review: bump RC packages, add shell tool to changelog
    
    - ag-ui: 1.0.0rc2 -> 1.0.0rc3
    - orchestrations: 1.0.0rc1 -> 1.0.0rc2
    - Add shell tool (#5664) to CHANGELOG
    - uv.lock refreshed
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Prevent duplicate system instructions in Python telemetry (#5981)
    * Initial plan
    
    * Fix duplicated system instructions in Python telemetry
    
    * Clarify telemetry message filtering
    
    * test: cover separate and in-history system messages
    
    * Clarify observability message logging split
    
    * Simplify observability logging serialization
    
    * Harden observability regression test
    
    * Reuse observability span message serialization
    
    * Clarify observability logging loops
    
    * Polish observability message serialization
    
    * Tighten observability zip checks
    
    * Refactor observability message capture loop
    
    * Fix telemetry logging for separate system instructions
    
    * Refine observability OTEL message typing
    
    * Restore prepended-instruction logging path in _capture_messages
    
    * Revert logging change in _capture_messages; keep chat-history-only logging
    
    ---------
    
    Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
  • Python: feat(foundry): add experimental hosted tool factories on FoundryChatClient (#5958)
    * feat(foundry): add experimental hosted tool factories on FoundryChatClient
    
    Adds eight new `@experimental` static factory methods on `FoundryChatClient`
    covering Foundry-hosted tools that previously had no helper:
    
    - get_azure_ai_search_tool
    - get_sharepoint_tool
    - get_fabric_tool
    - get_memory_search_tool
    - get_computer_use_tool
    - get_browser_automation_tool
    - get_bing_custom_search_tool
    - get_a2a_tool
    
    All factories are marked with the new `ExperimentalFeature.FOUNDRY_TOOLS` tag
    and resolve the underlying `azure-ai-projects` preview classes lazily through
    a `_require_sdk_class` helper so older SDK versions still import cleanly and
    fail with a clear `ImportError` only on use.
    
    Tests cover each factory's return type and field wiring, the experimental
    metadata, and the missing-SDK-class fallback.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * test(foundry): address review comments on tool-factory tests
    
    * Skip preview-tool tests gracefully (`_skip_if_sdk_class_missing`) when
      the installed `azure-ai-projects` does not expose the required preview
      class, matching the lazy-import guard in production code so the test
      suite stays green on older SDK installs.
    * Add `filterwarnings("ignore::FutureWarning")` to each new tool-factory
      test (and the parametrized metadata test) so they remain stable under
      strict warning configurations \u2014 the global dedup in
      `_feature_stage._WARNED_FEATURES` makes `pytest.warns` brittle across
      ordered runs.
    * Use `monkeypatch.setattr(..., None, raising=False)` instead of
      `delattr` in the missing-SDK-class test so it works for modules that
      implement PEP 562 `__getattr__`.
    * Split the long `get_bing_custom_search_tool` return into two lines for
      readability.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): harden tool-factory kwargs against silent override
    
    * Reorder the dict-literal kwargs assembly in get_azure_ai_search_tool,
      get_memory_search_tool, and get_bing_custom_search_tool so explicit
      parameters always take precedence over **kwargs (matching the safe
      pattern already used in get_a2a_tool). This prevents a caller
      passing `project_connection_id`, `index_name`, `memory_store_name`,
      `scope`, or `instance_name` through `**kwargs` from silently
      overriding the explicit security-sensitive arguments.
    * Update the README experimental note to reflect once-per-feature-id
      dedup semantics of `_feature_stage._WARNED_FEATURES` rather than
      claiming a per-factory "first use" warning.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * feat(foundry): split FOUNDRY_TOOLS / FOUNDRY_PREVIEW_TOOLS, add bing-grounding
    
    - Add ExperimentalFeature.FOUNDRY_PREVIEW_TOOLS to distinguish wrappers around
      preview Foundry SDK tool classes (Sharepoint/Fabric/Memory/ComputerUse/
      BrowserAutomation/BingCustomSearch/A2A) from FOUNDRY_TOOLS, which is for
      GA-SDK wrappers that are simply new in agent-framework-foundry
      (AzureAISearch, BingGrounding).
    - Add get_bing_grounding_tool factory and a 'Choosing a web grounding tool'
      comparison block on get_web_search_tool / get_bing_grounding_tool /
      get_bing_custom_search_tool docstrings.
    - Drop the _require_sdk_class lazy resolver: every guarded class is available
      at azure-ai-projects>=2.1.0 (the package floor), so import them eagerly.
      Concrete return types replace 'Any'.
    - README: split the experimental factories into two tables, one per feature
      flag, with a note explaining the distinction.
    - Tests: split into FOUNDRY_TOOLS / FOUNDRY_PREVIEW_TOOLS factory cases;
      drop the obsolete missing-SDK-class ImportError test.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • [BREAKING] Python: Enable instrumentation by default (#5865)
    * Enable instrumentation by default
    
    * Update samples
    
    * Optimization when span is not recording
    
    * Address Copilot comments
    
    * Revert uv.lock
    
    * Add warning
    
    * Formatting
    
    * Fix mypy
    
    * Add disable_instrumentation() with sticky user-intent semantics
    
    Add a public disable_instrumentation() entry point so users can explicitly opt
    out of Agent Framework telemetry, with a sticky-disable flag that makes the
    user's intent "leading" — no framework code path (foundry's
    configure_azure_monitor, configure_otel_providers, enable_instrumentation,
    enable_sensitive_telemetry, or direct OBSERVABILITY_SETTINGS.enable_*
    writes) can re-enable instrumentation until the user explicitly clears the
    disable with enable_instrumentation(force=True) /
    enable_sensitive_telemetry(force=True).
    
    Also addresses the two remaining unresolved review threads on the PR:
    1. test_observability_settings_defaults_instrumentation_true pins the new
       "ENABLE_INSTRUMENTATION defaults to True when env unset" behavior.
    2. test_enable_instrumentation_reads_env_sensitive_data restores coverage
       for the post-import load_dotenv() fallback path.
    
    Implementation:
    - ObservabilitySettings.enable_instrumentation / enable_sensitive_data become
      properties backed by _enable_*. While _user_disabled is True, the getters
      return False and the setters drop True writes (defense in depth so third-
      party writes can't subvert the disable).
    - Public is_user_disabled read-only property lets integrations (e.g. foundry's
      configure_azure_monitor) cheaply check the disable state without poking at
      privates.
    - enable_instrumentation() and enable_sensitive_telemetry() short-circuit with
      an info log when disabled; gain a force=True kwarg that clears the disable.
    - configure_otel_providers() still creates providers / exporters / views so a
      later force-enable can use them, but logs an info message when called while
      disabled.
    - Foundry's FoundryChatClient.configure_azure_monitor and
      FoundryAgent.configure_azure_monitor early-return when the user has
      disabled, so Azure Monitor's global providers aren't installed unnecessarily.
    
    Tests: 11 new tests covering default-on, env re-read at call time, sticky
    behavior against each re-enable surface (enable_instrumentation,
    enable_sensitive_telemetry, configure_otel_providers, direct attribute
    writes), force=True override, re-arming the disable, and the __all__ export.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs: document disable_instrumentation() and force=True paths
    
    Add a "Disabling instrumentation" section to the observability sample README
    that walks through:
    
    - The distinction between the ENABLE_INSTRUMENTATION env var (initial,
      non-sticky) and disable_instrumentation() (process-wide, sticky).
    - Why the sticky semantics matter: framework integrations like
      FoundryChatClient.configure_azure_monitor() can call
      enable_instrumentation() as part of their setup, and the user's opt-out
      needs to win.
    - All five surfaces guarded by the sticky disable (property reads, public
      enable functions, configure_otel_providers, direct attribute writes,
      is_user_disabled-aware integrations).
    - The force=True escape hatch on both enable_instrumentation() and
      enable_sensitive_telemetry().
    - How third-party integrations should consult OBSERVABILITY_SETTINGS.is_user_disabled.
    - The limits of the disable (does not tear down existing providers /
      in-flight spans / third-party instrumentation, does not persist across
      processes).
    
    Cross-links the new section from the ENABLE_INSTRUMENTATION row in the env
    vars table.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs: soften disable_instrumentation() overclaim about telemetry guarantees
    
    Replace 'no telemetry will be emitted no matter what' (which is too strong,
    since callers can still pass force=True or mutate private attributes) with
    language framing the disable as a user-intent contract that library and
    framework code is expected to honor: the framework actively short-circuits
    the public enable paths, force=True and private-attribute writes are
    acknowledged as out-of-contract escape hatches that integrations should
    not use on the user's behalf.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs: correct observability Dependencies section
    
    - opentelemetry-sdk is no longer a hard dependency; it is lazily imported by
      create_resource(), create_metric_views(), and configure_otel_providers()
      with a clear ImportError when missing. Day-to-day instrumentation works
      with opentelemetry-api alone provided some other component configures the
      global OpenTelemetry providers (Azure Monitor, an APM agent, application
      bootstrap, etc.).
    - opentelemetry-semantic-conventions-ai is no longer used anywhere in the
      source; remove it from the listed dependencies.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * docs: replace stale observability migration guide with current PR's only relevant migration
    
    The old guide documented the move away from setup_observability(otlp_endpoint=...)
    which was an earlier-release API change unrelated to this PR and stale enough that
    it's more confusing than helpful at this point. Replace it with a short note on the
    single migration this PR introduces: callers of
    enable_instrumentation(enable_sensitive_data=True) should switch to
    enable_sensitive_telemetry(). Cross-link to the Disabling instrumentation section
    for the rare 'force on without enabling sensitive data' use case where
    enable_instrumentation() still applies.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Skip MCP prompt loading when unsupported (#5370)
    * Python: Skip MCP prompt loading when unsupported
    
    * Fix MCP pagination pyright checks
    
    * Simplify MCP support flag checks
  • Python: Bump Python package versions for a release (#5964)
    * Bump Python package versions to 1.5.0 for a release
    
    * Promote orchestrations to 1.0.0rc1
    
    * ci(python-setup): merge dynamic exclude into existing workspace exclude
    
    The python-setup action injected exclude = [...] verbatim into
    [tool.uv.workspace], producing a duplicate 'exclude' key when the
    section already had a static exclude. Scope the rewrite to the
    [tool.uv.workspace] section and append the package to the existing
    array when present; idempotent if the package is already excluded.
    
    * Address Copilot review feedback: raise inter-package floors to 1.5.0
    
    - foundry, foundry-local: agent-framework-openai >=1.4.0 -> >=1.5.0
    - azure-contentunderstanding: agent-framework-foundry >=1.4.0 -> >=1.5.0
    - azurefunctions: pin agent-framework-durabletask to >=1.0.0b260519,<2
    
    Keeps lockstep cohort consistent and avoids mixed 1.4.x / 1.5.0 installs.
    
    * Re-include azurefunctions and durabletask in the uv workspace
    
    The pinned durabletask>=1.4.0 floor is enough to make resolution succeed;
    the workspace exclude was over-correction and broke CI samples and pyright
    type-checking (re-exports in agent_framework/azure/__init__.pyi plus
    samples/04-hosting/{azure_functions,durabletask}/ could not resolve their
    imports). Dropping them from agent-framework-core[all] still stands so the
    metapackage does not pull them.
    
    * Restore azurefunctions and durabletask in agent-framework-core[all]
    
    The durabletask floor pin keeps users on the safe 1.4.0, so they are once
    again included in the metapackage. Update CHANGELOG to reflect the pin
    rather than an [all] removal.
    
    * Raise uvicorn ceiling in ag-ui and devui to allow 0.42+
    
    The root override-dependencies pins uvicorn[standard]>=0.34.0 (no upper)
    and the workspace lock resolves to 0.47.0. The package ceiling <0.42.0
    meant the workspace was no longer testing the declared supported range.
    Bump to <1 so the lock fits within the declared bounds.
    
    Also picked up by validate-dependency-bounds: refresh stale orchestrations
    RC pin in devui dev deps.
  • Python: Record actual served model from Azure OpenAI (#5910)
    * Record actual served model as response model for Azure OpenAI
    
    * Formatting
    
    * Fix tests
    
    * Fix pipeline error
    
    * Comments
    
    * Address review: surface served model via ChatResponse.model
    
    Apply blocking review feedback from PR #5910:
    
    - Use ChatResponse.model / ChatResponseUpdate.model as the source of truth
      for the Azure x-ms-served-model header value, instead of stashing it in
      additional_properties and overriding it again in observability.
      Observability already reads response.model; the chat client now overwrites
      it post-parse when the served-model header is present. Empirically the
      Azure Responses API returns the deployment alias in body.model and the
      actual snapshot (e.g. gpt-5-nano-2025-08-07) in this header.
    
    - Move the AZURE_OPENAI_SERVED_MODEL_HEADER constant out of observability.py
      and into RawOpenAIChatClient (as the SERVED_MODEL_HEADER ClassVar). The
      header is Azure-OpenAI-Responses-API-specific so observability does not
      need to know about it.
    
    - Revert the streaming text_format path to client.responses.stream(...) and
      drop the _pydantic_model_to_text_format_param helper. That helper imported
      from openai.lib._parsing._responses (a private SDK path) and the swap to
      responses.create(stream=True) dropped client-side output_parsed for
      structured-output streaming. The streaming-with-text_format path is the
      only one that does not surface the served-model header - documented inline.
    
    - Wrap the raw streaming responses in async with so the underlying socket
      closes deterministically (continuation_token retrieve + create paths).
    
    - Fix the empty-string / whitespace-only header at the source by stripping
      in _extract_served_model and returning None when nothing remains.
    
    - Revert unrelated formatting-only churn in _skills.py and test_mcp.py.
    
    - Update unit tests to assert against chat_response.model / update.model
      and add an aggregated streaming assertion plus a pin that the
      streaming-with-text_format path does not get the header.
    
    Verified end-to-end against Azure OpenAI Responses API: deployment alias
    gpt-5-nano now reports gpt-5-nano-2025-08-07 as ChatResponse.model in both
    the non-streaming and streaming paths.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: preserve streaming structured output finalization
    
    Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
    
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
    
    * refactor: name streaming response finalizer
    
    Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
    
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
    
    * fix: capture streaming response format after prepare
    
    Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
    
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
    
    * refactor: clarify streaming response format capture
    
    Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
    
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
    
    * test: use public API for streaming structured output
    
    Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
    
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
    
    * Inline the served-model header override at its two call sites
    
    The `_apply_served_model_header` helper was a 1-line wrapper around
    `_extract_served_model`. Inlining the `if served_model is not None: ...`
    matches the pattern already used in the streaming paths and folds the
    explanatory docstring onto `_extract_served_model` (which is now the
    single place that knows about the header).
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
    Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
  • Python: Improve the handling of intermediate outputs for workflows and orchestrations (#5623)
    * Improve the handling of intermediate outputs for workflows and orchestrations
    
    * Address PR review feedback on intermediate output forwarding
    
    - Switch workflow.as_agent() forwarding to an explicit allowlist of {output,
      intermediate, data, request_info} so orchestration-internal events
      (group_chat, handoff_sent, magentic_orchestrator) stay inside the workflow
      instead of leaking into agent responses via str(data) coercion.
    - Stop raising on intermediate AgentResponseUpdate in non-streaming run();
      surface the partial as a Message with text_reasoning content. The defensive
      raise still applies to terminal output events, where Update payloads would
      corrupt message ordering.
    - Extend the DevUI workflow-event mapper so intermediate yields wrapping
      plain strings, Messages, and list[Message] render as visible output items
      instead of generic completed-trace events.
    - Add orchestration coverage for GroupChat, Handoff, and Magentic builders
      (default vs intermediate_outputs=True; structural where end-to-end is heavy).
    
    * Lift output-designation policy into a value type
    
    Replace the ``Workflow._output_executors`` list and the
    ``RunnerContext.should_label_as_intermediate`` Protocol method with a single
    immutable ``OutputDesignation`` value type owned by ``Workflow``. Thread the
    designation as a parameter through the existing call chain (Runner ->
    EdgeRunner -> Executor -> WorkflowContext) so ``yield_output`` consults the
    threaded snapshot directly rather than calling back into the runner context.
    
    Removes the ``InProcRunnerContext._workflow`` back-reference and the
    ``WorkflowBuilder.build()`` assignment that wired it up. Adds the public
    predicate ``Workflow.is_terminal_executor(executor_id)`` for external
    observers; ``OutputDesignation`` itself stays package-internal.
    
    Key decisions
    - ``OutputDesignation.designated`` is ``frozenset[str] | None`` -- ``None``
      preserves legacy "every yield is type='output'" behavior, any frozenset
      (including empty) opts into strict mode. The ``DeprecationWarning`` for
      legacy mode at build time is unchanged.
    - ``output_designation`` is an optional parameter on ``Runner``,
      ``EdgeRunner.send_message``, ``EdgeRunner._execute_on_target``,
      ``Executor.execute``, ``Executor._create_context_for_handler``, and
      ``WorkflowContext.__init__``. Each defaults to legacy ``OutputDesignation()``
      so direct callers (Azure Functions ``CapturingRunnerContext``,
      ``test_runner`` recording fixtures) keep working without ceremony.
    - The workflow-level filter in ``_run_core`` reads ``self._output_designation``
      live, preserving today's semantics where mutating the designation after
      build still affects subsequent runs (used by two existing tests).
    - ``Workflow.to_dict()`` continues to emit ``"output_executors":
      list[str] | None`` (sorted from the frozenset). Checkpoint format unchanged.
    
    Files changed
    - _workflow.py: add ``OutputDesignation`` dataclass; replace
      ``_output_executors`` with ``_output_designation``; add
      ``is_terminal_executor``; delete ``_should_yield_output_event``.
    - _runner_context.py: drop ``should_label_as_intermediate`` Protocol method
      and ``InProcRunnerContext`` impl; drop ``_workflow`` back-reference.
    - _workflow_builder.py: remove ``context._workflow = workflow`` assignment.
    - _runner.py, _edge_runner.py, _executor.py, _workflow_context.py: thread
      ``output_designation`` parameter through the call chain.
    - tests/workflow/test_output_designation.py (new): three-state coverage of
      the value type plus the public predicate delegation.
    - tests/workflow/test_workflow_builder.py, test_validation.py,
      test_workflow.py, test_runner.py and
      orchestrations/tests/test_orchestration_intermediate_vs_terminal.py:
      switch probes from ``_output_executors`` set checks to
      ``get_output_executors`` / ``is_terminal_executor``; update two
      post-build mutation tests to set ``_output_designation`` instead.
    
    Verification
    - core/tests/workflow/, orchestrations/tests/, azurefunctions/tests/:
      1119 passed, 42 skipped, 2 xfailed.
    - ``uv run poe lint``: clean.
    - ``uv run poe typing``: only the pre-existing
      ``_AGENT_FORWARDED_EVENT_TYPES`` pyright warning from 394bcd607 remains.
    
    Notes for next iteration
    - The builder's own ``_output_executors`` attribute (``list[Executor |
      SupportsAgentRun]``) is intentionally untouched; the issue scoped the
      rename to the workflow attribute.
    - Adjacent review candidates (twin ``WorkflowAgent`` translators,
      ``_AGENT_FORWARDED_EVENT_TYPES`` kind classifier,
      ``_event_origin_context`` ContextVar removal, ``WorkflowEvent`` ADT
      split, legacy-mode removal) remain out of scope.
    
    * Add explicit workflow output designation
    
    Key decisions
    
    - Extend the internal OutputDesignation value type from terminal-only membership to output/intermediate/hidden classification. Legacy mode remains outputs=None, so workflows built without output_executors or intermediate_executors still label every yield_output as type='output'.
    
    - WorkflowBuilder now accepts intermediate_executors. Providing either designation enters explicit mode; output executors emit output, intermediate executors emit intermediate, and unlisted yield_output payloads are hidden from caller-facing events while remaining in executor_completed data.
    
    - Empty explicit designation, duplicate entries, overlaps, unknown executors, and designated executors without workflow output annotations fail build validation. Existing orchestration builders pass intermediate-capable participants through intermediate_executors to preserve current intermediate_outputs behavior until participant-oriented designation lands.
    
    Files changed
    
    - packages/core/agent_framework/_workflows/_workflow.py, _workflow_builder.py, _workflow_context.py, _validation.py, _events.py
    
    - packages/core/tests/workflow/test_output_designation.py, test_output_executors_contract.py, test_strict_mode_event_labeling.py, test_validation.py, test_workflow.py, test_workflow_agent_intermediate.py
    
    - packages/orchestrations/agent_framework_orchestrations/_sequential.py, _concurrent.py, _group_chat.py, _magentic.py
    
    - packages/core/AGENTS.md
    
    Verification
    
    - uv run pytest packages/core/tests/workflow packages/orchestrations/tests packages/devui/tests/devui/test_mapper.py -q
    
    - uv run pytest packages/azurefunctions/tests -q
    
    - uv run poe lint
    
    - uv run poe typing fails only on pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error.
    
    Notes for next iteration
    
    - issues/03-core-workflow-explicit-designation.md was moved to issues/done but issues/ remains untracked and intentionally excluded from this commit.
    
    - Slice 4 should tighten workflow.as_agent() mapping for hidden emissions and streaming-only update payloads; Slice 5 should replace orchestration intermediate_outputs with participant-oriented designation.
    
    * Tighten workflow-as-agent output mapping
    
    Key decisions
    
    - Treat AgentResponseUpdate as a streaming-only payload across the workflow.as_agent() adapter, so non-streaming agent runs now reject both terminal output and intermediate workflow events carrying updates.
    - Keep streaming classification behavior explicit: terminal update payloads remain normal text content, while intermediate update payloads are rewritten to text_reasoning content.
    - Add explicit-mode coverage proving hidden yield_output emissions do not appear in non-streaming AgentResponse messages or streaming AgentResponseUpdate chunks.
    
    Files changed
    
    - packages/core/agent_framework/_workflows/_agent.py
    - packages/core/tests/workflow/test_workflow_agent_intermediate.py
    
    Verification
    
    - uv run pytest packages/core/tests/workflow/test_workflow_agent_intermediate.py -q
    - uv run pytest packages/core/tests/workflow/test_workflow_agent.py packages/core/tests/workflow/test_workflow_agent_intermediate.py -q
    - uv run pytest packages/core/tests/workflow packages/orchestrations/tests packages/devui/tests/devui/test_mapper.py -q
    - uv run poe lint
    - uv run poe typing fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error.
    
    Blockers or notes for next iteration
    
    - issues/04-workflow-as-agent-output-mapping.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit.
    - Slice 5 should replace orchestration intermediate_outputs with participant-oriented designation.
    
    * Add orchestration participant output designation
    
    Key decisions
    
    - Replace orchestration intermediate_outputs with participant-oriented output_participants and intermediate_participants across Sequential, Concurrent, GroupChat, Magentic, and Handoff builders.
    - Keep synthetic final executors terminal by default for Concurrent, GroupChat, and Magentic; keep Sequential's final participant terminal by default; keep Handoff participants terminal by default.
    - Centralize participant designation validation for empty explicit designation, duplicates, overlaps, and unknown participants, then map validated participants to workflow output/intermediate executors.
    
    Files changed
    
    - packages/orchestrations/agent_framework_orchestrations/_participant_designation.py
    - packages/orchestrations/agent_framework_orchestrations/_sequential.py
    - packages/orchestrations/agent_framework_orchestrations/_concurrent.py
    - packages/orchestrations/agent_framework_orchestrations/_group_chat.py
    - packages/orchestrations/agent_framework_orchestrations/_magentic.py
    - packages/orchestrations/agent_framework_orchestrations/_handoff.py
    - packages/orchestrations/tests/test_orchestration_intermediate_vs_terminal.py
    - packages/orchestrations/tests/test_magentic.py
    
    Blockers or notes for next iteration
    
    - issues/05-orchestration-participant-designation.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit.
    - Slice 7 should migrate samples and docs away from intermediate_outputs to the new participant designation API.
    - uv run poe typing still fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error.
    
    * Migrate samples to explicit output designation
    
    Key decisions
    
    - Replace sample usage of the removed orchestration intermediate_outputs boolean with participant-oriented intermediate_participants designation.
    - Update raw workflow guidance to show output_executors together with intermediate_executors, and document that unlisted yields are hidden in explicit designation mode.
    - Keep orchestration final outputs terminal while streaming designated participant responses as intermediate progress, including workflow.as_agent() samples where intermediates map to text_reasoning content.
    - Refresh workflow and orchestration README guidance plus the changelog reference so public docs no longer point users at intermediate_outputs.
    
    Files changed
    
    - CHANGELOG.md
    - packages/orchestrations/README.md
    - samples/README.md
    - samples/03-workflows/README.md
    - samples/03-workflows/control-flow/intermediate_vs_terminal_outputs.py
    - samples/03-workflows/orchestrations/README.md
    - samples/03-workflows/orchestrations/group_chat_agent_manager.py
    - samples/03-workflows/orchestrations/group_chat_philosophical_debate.py
    - samples/03-workflows/orchestrations/group_chat_simple_selector.py
    - samples/03-workflows/orchestrations/magentic.py
    - samples/03-workflows/orchestrations/magentic_human_plan_review.py
    - samples/03-workflows/orchestrations/sequential_chain_only_agent_responses.py
    - samples/03-workflows/agents/group_chat_workflow_as_agent.py
    - samples/03-workflows/agents/magentic_workflow_as_agent.py
    - samples/03-workflows/agents/sequential_workflow_as_agent.py
    - samples/semantic-kernel-migration/orchestrations/group_chat.py
    - samples/semantic-kernel-migration/orchestrations/magentic.py
    
    Blockers or notes for next iteration
    
    - issues/07-samples-and-docs-explicit-output-designation.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit.
    - issues/06-devui-intermediate-event-rendering.md remains present and appears already satisfied by existing DevUI mapper/tests from the prior implementation slice.
    - PRD-explicit-workflow-output-designation.md remains untracked and intentionally excluded from this commit.
    
    * Render DevUI intermediate workflow outputs
    
    Key decisions
    
    - Preserve workflow output designation metadata on visible DevUI output messages and text deltas so intermediate/data emissions remain distinguishable from terminal output.
    - Render intermediate workflow message items in the execution timeline using executor metadata, while excluding them from the final workflow result aggregation.
    - Keep terminal output message rendering unchanged and retain legacy data events on the intermediate compatibility path.
    
    Files changed
    
    - packages/devui/agent_framework_devui/_mapper.py
    - packages/devui/frontend/src/components/features/workflow/execution-timeline.tsx
    - packages/devui/frontend/src/components/features/workflow/workflow-view.tsx
    - packages/devui/frontend/src/types/openai.ts
    - packages/devui/tests/devui/test_mapper.py
    
    Blockers or notes for next iteration
    
    - issues/06-devui-intermediate-event-rendering.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit.
    - PRD-explicit-workflow-output-designation.md remains untracked and intentionally excluded from this commit.
    - uv run poe typing still fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error.
    
    * Fix mypy
    
    * Clarify orchestration participant output config
    
    * Rename participant output kwargs for clarity
    
    output_participants -> final_output_from, intermediate_participants ->
    intermediate_output_from. The old names read like categories of
    participant; the new names make it clear the kwarg designates which
    participants' outputs surface as final vs. intermediate events.
    
    * Rename core workflow output kwargs with deprecation shim
    
    Adds final_output_from / intermediate_output_from as canonical kwargs on
    Workflow and WorkflowBuilder. Old output_executors / intermediate_executors
    kwargs continue to work but emit DeprecationWarning via a shared coalesce
    helper that also rejects supplying both. Wire-format keys in to_dict()
    stay as output_executors / intermediate_executors so checkpoint
    compatibility is preserved.
    
    Internal call sites in orchestrations and samples updated to the new
    names so users following sample code learn the canonical vocabulary;
    legacy callers still work with a one-shot warning.
    
    * Suppress pyright reportPrivateUsage on cross-module sentinel import
    
    * Update docstrings
    
    * Propagate sub-workflow intermediate outputs, fix handoff/sequential intermediate-only designation, and shore up tests, sample, and docstrings around the intermediate output contract.
    
    * Add canonical workflow output_from selection
    
    Key decisions:\n- Make output_from the canonical workflow-output allow-list and keep output_executors/final_output_from as deprecated compatibility aliases.\n- Treat empty output_from/intermediate_output_from lists as explicit selections and keep validation responsible for empty, duplicate, overlap, and unknown selections.\n- Remove the branch-only public intermediate_executors WorkflowBuilder kwarg while preserving legacy wire keys in to_dict().\n\nFiles changed:\n- packages/core/agent_framework/_workflows/_workflow.py\n- packages/core/agent_framework/_workflows/_workflow_builder.py\n- packages/core/agent_framework/_workflows/_workflow_context.py\n- packages/core/agent_framework/_workflows/_agent.py\n- packages/core/agent_framework/_workflows/_agent_executor.py\n- packages/core/tests/workflow/* output-selection coverage updates\n- packages/core/AGENTS.md\n- issues/done/001-canonical-list-based-output-selection.md\n\nBlockers/notes:\n- Orchestration builders still pass final_output_from internally; follow-up issue 004 should migrate them to output_from.\n- Legacy omitted-selection behavior and explicit all/all_other literals are left for issues 002 and 003.
    
    * Add explicit all workflow output selection
    
    Key decisions:
    - Treat output_from='all' as an explicit workflow-output selection sentinel and expand it at build time to executors with declared workflow output types.
    - Keep omitted output selections in legacy all-output mode with a deprecation warning that names output_from and intermediate_output_from and points to output_from='all'.
    - Reject intermediate_output_from='all' at construction because the all-output literal is output-only for this issue.
    
    Files changed:
    - packages/core/agent_framework/_workflows/_workflow_builder.py
    - packages/core/tests/workflow/test_output_executors_contract.py
    - issues/done/002-explicit-all-output-and-legacy-migration.md
    
    Blockers/notes:
    - all_other intermediate-output selection remains for issue 003.
    - Workflow-as-agent/orchestration parity remains for issue 004.
    
    * Add all-other intermediate output selection
    
    Key decisions:
    - Treat intermediate_output_from='all_other' as an explicit intermediate-output selection sentinel and expand it at build time after the workflow graph is complete.
    - Expand all_other to output-capable executors not selected by output_from; omitted or empty output_from selects no workflow outputs, while output_from='all' leaves an empty intermediate selection.
    - Keep output_from='all_other' invalid so all_other remains intermediate-output-only and runtime classification still receives concrete executor-id sets.
    
    Files changed:
    - packages/core/agent_framework/_workflows/_workflow_builder.py
    - packages/core/tests/workflow/test_output_executors_contract.py
    - issues/done/003-all-other-intermediate-output-selection.md
    
    Blockers/notes:
    - Workflow-as-agent and orchestration parity remains for issue 004.
    - Full documentation updates remain for issue 005.
    
    * Add orchestration output selection parity
    
    Key decisions:
    - Expose output_from on sequential, concurrent, group chat, handoff, and magentic builders while keeping final_output_from as a deprecated compatibility alias.
    - Resolve orchestration participant selections through the same explicit rules as workflows: output_from='all', intermediate_output_from='all_other', hidden unselected participant payloads, and overlap/duplicate/unknown/invalid-literal validation.
    - Continue preserving documented orchestration defaults by always designating each pattern's terminal internal executor where applicable.
    
    Files changed:
    - packages/orchestrations/agent_framework_orchestrations/_participant_output_config.py
    - packages/orchestrations/agent_framework_orchestrations/_sequential.py
    - packages/orchestrations/agent_framework_orchestrations/_concurrent.py
    - packages/orchestrations/agent_framework_orchestrations/_group_chat.py
    - packages/orchestrations/agent_framework_orchestrations/_handoff.py
    - packages/orchestrations/agent_framework_orchestrations/_magentic.py
    - packages/orchestrations/agent_framework_orchestrations/_orchestration_request_info.py
    - packages/orchestrations/tests/test_orchestration_intermediate_vs_terminal.py
    - issues/done/004-workflow-as-agent-and-orchestration-parity.md
    
    Blockers/notes:
    - Full documentation and sample migration wording remains for issue 005.
    - Existing tests that intentionally use final_output_from now emit the new deprecation warning.
    
    * Document workflow output selection contract
    
    Key decisions:
    - Use Workflow Output and Intermediate Output as the developer-facing terms for selected caller-facing emissions.
    - Document output_from and intermediate_output_from as the canonical API, with output_from as an allow-list and unselected payloads hidden unless explicitly selected as intermediate.
    - Add scenario and invalid-selection tables for workflow and orchestration docs, including legacy omission warnings, output_from='all', intermediate_output_from='all_other', list selections, invalid literals, overlap, duplicates, unknown selections, and empty explicit selections.
    - Migrate samples away from final_output_from and output_executors except where compatibility aliases are explicitly documented.
    
    Files changed:
    - packages/core/AGENTS.md
    - packages/orchestrations/README.md
    - packages/orchestrations/agent_framework_orchestrations/_handoff.py
    - packages/orchestrations/agent_framework_orchestrations/_sequential.py
    - samples/03-workflows/README.md
    - samples/03-workflows/control-flow/intermediate_vs_terminal_outputs.py
    - samples/03-workflows/human-in-the-loop/agents_with_approval_requests.py
    - samples/03-workflows/orchestrations/README.md
    - samples/04-hosting/foundry-hosted-agents/responses/05_workflows/main.py
    - scripts/sample_validation/create_dynamic_workflow_executor.py
    - issues/done/005-document-output-selection-contract.md
    
    Blockers/notes:
    - Direct full Ruff on scripts/sample_validation/create_dynamic_workflow_executor.py still reports pre-existing docstring/print/line-length issues outside this docs migration; syntax-focused checks for changed files pass.
    - No remaining AFK issue files are present under issues/.
    
    * Latest updates
    
    * Typing fixes
    
    * Cleanup
  • Python: Parse YAML block scalars in SKILL.md frontmatter (#5863)
    The frontmatter parser previously matched only single-line `key: value` pairs, so block scalar indicators (`|` literal, `>` folded, with chomping `-`/`+`) were silently truncated to the indicator character. Multi-line descriptions like `description: >\n  ...` lost their content.
    
    Add `_parse_yaml_scalar_value()` which detects block scalar indicators, collects indented continuation lines, strips the common leading indentation, joins per scalar style (newlines for `|`, spaces for `>`), and applies chomping per the YAML 1.2 spec. Update `_extract_frontmatter()` to use the helper for unquoted values.
    
    Adds 15 unit tests covering literal/folded styles, all chomping variants, indentation handling, content containing colons, non-description fields, tab indentation, blank-line preservation, and a regression test for plain values.
    
    Fixes #5713.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: bump package versions for 1.4.0 release (#5872)
    * fixes
    
    * fixes
    
    * Python: bump package versions for 1.4.0 release
    
    Cuts the python-1.4.0 release. MINOR bump on the released cohort
    (agent-framework, agent-framework-core, agent-framework-openai,
    agent-framework-foundry: 1.3.0 -> 1.4.0), driven by breaking changes
    in experimental skills API and new features. All 21 beta packages
    stamp 1.0.0b260514, all 3 alpha packages stamp 1.0.0a260514, and
    ag-ui remains at 1.0.0rc1 (freshly promoted). Date stamp reflects
    2026-05-14 Pacific.
    
    - Released cohort: 1.3.0 -> 1.4.0
    - Beta packages (21): 1.0.0b260507 -> 1.0.0b260514
    - Alpha packages (3): 1.0.0a260507 -> 1.0.0a260514
    - ag-ui: stays at 1.0.0rc1 (dep bound updated only)
    - Inter-package dependency lower bounds updated (>=1.3.0 -> >=1.4.0)
    - Fix chatkit StructuredInputItem exhaustiveness for openai-chatkit 1.6.4
    - Update CHANGELOG compare links
    - uv.lock refreshed
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: forward MCP tool call metadata (#5815)
    * Python: forward MCP tool call metadata
    
    * fix: preserve MCP tool meta after prompt reload
  • Python: Support list[str] arguments for file-based skill scripts (#5850)
    Port of .NET PR #5475. Broadens the args type from dict[str, Any] | None
    to dict[str, Any] | list[str] | None across the skill script API surface,
    enabling CLI-style argv forwarding to subprocess scripts.
    
    Changes:
    - SkillScript.run(), InlineSkillScript.run(), FileSkillScript.run(): widen
      args type; InlineSkillScript rejects list with TypeError
    - FileSkillScript.parameters_schema: returns array-of-strings schema
    - FileSkill.content: appends <scripts> block with parameters_schema
    - SkillScriptRunner protocol: widen args type
    - SkillsProvider._run_skill_script: widen args type
    - run_skill_script tool schema: accept object, array, or null
    - subprocess_script_runner sample: accept list[str], reject dict
    - class_based_skill sample: fix missing SkillFrontmatter wrapper
    - Standardize 'folder' to 'directory' in docstrings (#5712)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • [BREAKING] Python: Align file skill folder discovery with agentskills.io spec (#5807)
    * Align Python FileSkillsSource with agentskills.io spec
    
    Update FileSkillsSource to scan spec-defined subdirectories instead of
    recursive rglob for resource and script discovery:
    
    - Resources: scan 'references/' and 'assets/' (was: entire skill tree)
    - Scripts: scan 'scripts/' (was: entire skill tree)
    - Add resource_directories and script_directories parameters for
      customization, with '.' root indicator for skill root files
    - Add directory validation: reject '..' traversal, absolute paths, empty
      names; normalize separators and deduplicate directories
    - Non-recursive scanning within each configured directory (top-level only)
    - Containment check validates files against target directory, not just
      skill root, for stronger path-traversal defense
    - Case-insensitive directory deduplication via os.path.normcase()
    - Cross-platform absolute path rejection in directory validation
    - Sort discovery results for stable ordering
    - Update SkillsProvider.from_paths() to pass new parameters through
    - Update all tests for new subdirectory-scoped discovery behavior
    
    Resolves #5711.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address PR review: tighten path validation and add containment guard
    
    - Narrow Windows absolute path check to proper drive-root pattern
      (re.match r'^[A-Za-z]:[/\\]') to avoid rejecting valid POSIX names
    - Add _is_path_within_directory guard before _has_symlink_in_path in
      both discovery methods to prevent ValueError on escaped paths
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Log warning on OSError during directory listing in skill discovery
    
    Address review comment: _discover_resource_files and _discover_script_files
    previously swallowed OSError silently when iterdir() failed. Now log a
    warning so permission errors and transient FS failures are visible
    instead of making resource/script directories silently disappear.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Strip server-issued response item IDs under storage (#3295) (#5690)
    Fixes microsoft/agent-framework#3295. When the OpenAI Responses chat
    client sends a request that carries previous_response_id / conversation_id
    / conversation, the server already has the prior turn's response items
    and rejects duplicates with "Duplicate item found with id fc_xxx". The
    chat client was re-sending them inline whenever the input messages still
    carried the items in additional_properties (workflow replay, history
    providers, etc.), which broke any tool-using agent with persistent
    history.
    
    Decisions:
    - Single chokepoint: _prepare_message_for_openai. When the resulting
      request uses service-side storage, drop function_call, reasoning,
      approval-request/response, and local-shell-call items from the wire
      input. Keep function_result with its call_id; the server pairs it to
      the prior function_call via that key.
    - function_result is preserved unconditionally except for the local-shell
      variant, which carries its own server-issued item id.
    - No public API change. Wire format change is subtractive and only on
      requests that would otherwise 400.
    - Re-pointed the strict-xfail in test_full_conversation.py from #4047 to
      #3295. Kept xfail because the test asserts executor-level session-id
      clearing, which is the defense-in-depth half tracked by 3295-03; this
      slice closes the wire-level half.
    
    Files:
    - python/packages/openai/agent_framework_openai/_chat_client.py: strip
      rule applied alongside the existing reasoning-item branch.
    - python/packages/openai/tests/openai/test_openai_chat_client.py: four
      new tests pin the contract (function_call, approval, local-shell-call
      stripped under storage; everything kept without storage). Updated
      pre-existing tests that exercised the storage-on path to either pass
      request_uses_service_side_storage=False explicitly or assert the new
      strip behavior.
    - python/packages/foundry/tests/foundry/test_foundry_chat_client.py:
      same explicit storage-off opt-in for the inherited test.
    - python/packages/core/tests/workflow/test_full_conversation.py:
      re-pointed xfail reason to #3295 and the executor-level follow-up.
    
    Notes for next iteration:
    - 3295-01 (HITL wire-format validation against live OpenAI/Foundry) was
      not run; it requires the user's API credentials. The PRD design is
      locked but the empirical confirmation is still pending. If script 3
      fails on either provider, this slice may need to be revisited.
    - 3295-03 (clear service_session_id in AgentExecutor on full-history
      replay) remains open. After it lands the xfail in
      test_full_conversation.py can be removed.
    - pytest was not run in this iteration because uv-based pytest commands
      required interactive approval. Validation rests on careful reading;
      next iteration should run the openai + core test suites.
  • [Python] [Breaking] Extract skill spec metadata into SkillFrontmatter (#5775)
    * Fix Skill docstring consistency and spelling
    
    - Add ClassSkill to Skill class docstring concrete implementations list
    - Normalize 'defence' to 'defense' for American English consistency
    - Remove extra blank line in InlineSkill docstring example
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix E501 line-too-long lint error in test_skills.py
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix stale test section header to reflect SkillFrontmatter API
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix metadata children overriding top-level frontmatter fields
    
    Scope YAML_KV_RE to column-0 keys only so indented children
    under metadata: are not mistakenly parsed as top-level fields.
    Add regression test and spec fields to sample SKILL.md files.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: fix: prevent MCP message_handler deadlock on notification reload (#4866)
    * fix(python): prevent MCP message_handler deadlock on notification reload
    
    When an MCP server sends a notifications/tools/list_changed or
    notifications/prompts/list_changed notification, the message_handler
    previously awaited load_tools()/load_prompts() directly. Since the
    handler runs on the MCP SDK's single-threaded receive loop, this
    caused a deadlock: load_tools() sends a list_tools request and waits
    for its response, but the receive loop cannot deliver that response
    while blocked in the handler.
    
    This manifested as a timeout in call_tool(), which then surfaced as
    "Error: Function failed." to the model instead of the real tool
    output. The MATLAB MCP server reliably triggers this because it sends
    a tools/list_changed notification during tool execution.
    
    Fix: schedule reloads as background asyncio.Tasks via a new
    _schedule_reload() helper, freeing the receive loop immediately.
    
    Fixes #4828
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address PR review feedback: fix exc_info, coalesce reloads, shutdown cleanup, tests
    
    - Fix exc_info=exc -> exc_info=True in _schedule_reload and message_handler
    - Tighten _schedule_reload param type from Any to Coroutine[Any, Any, None]
    - Coalesce reloads: cancel-and-replace per reload kind to prevent unbounded growth
    - Cancel pending reload tasks in _close_on_owner before tearing down session
    - Re-raise CancelledError in _safe_reload to respect task cancellation
    - Replace flaky asyncio.sleep(0) with asyncio.wait_for/gather in tests
    - Add caplog assertions to verify reload failure is actually logged
    - Assert _pending_reload_tasks cleanup on error path
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: address review comments on MCP reload handling
    
    - Fix exc_info=True -> exc_info=message in message_handler error logging,
      since the handler is not called from an except block
    - Await cancelled reload tasks in _close_on_owner before tearing down
      the session to avoid 'Task was destroyed but pending' warnings
    - Add cancel-and-replace test verifying duplicate notifications cancel
      the first reload task and only keep one in flight
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: remove Task.cancelling() call for Python 3.10 compat
    
    Task.cancelling() was added in Python 3.11. Replace with awaiting
    the task and checking cancelled() instead.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Add debug log when cancelling superseded reload task
    
    Log at DEBUG level when a new notification cancels an in-flight reload
    task, improving observability of the cancel-and-replace behavior.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <copilot@github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: bump package versions for 1.3.0 release (#5706)
    * Python: bump package versions for 1.3.0 release
    
    MINOR bump on the released cohort (agent-framework, agent-framework-core,
    agent-framework-openai, agent-framework-foundry: 1.2.2 -> 1.3.0). All 22
    beta packages stamp 1.0.0b260507 and all 3 alpha packages stamp
    1.0.0a260507 per the lockstep convention. Date stamp reflects 2026-05-07
    Pacific.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review: bump foundry_local openai floor, fix devui orchestrations pin, clarify breaking scope
    
    - foundry_local: bump agent-framework-openai lower bound from >=1.1.0 to >=1.3.0
    - devui: update stale agent-framework-orchestrations dev pin from 1.0.0b260402 to 1.0.0b260507
    - CHANGELOG: clarify [BREAKING] applies to experimental skills API only
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Revert devui orchestrations pin to 1.0.0b260402 to avoid breaking DevUI
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Add ClassSkill for class-based skill definitions (#5678)
    * Python: Add ClassSkill for class-based skill definitions
    
    Add ClassSkill abstract base class with decorator-based resource and script
    discovery, porting .NET's AgentClassSkill (PRs #5027 and #5183) to Python.
    
    - Add ClassSkill(Skill, ABC) with instructions abstract property, cached
      content/resources/scripts properties
    - Add @ClassSkill.resource and @ClassSkill.script static method decorators
      for auto-discovery of methods and properties
    - Extract _build_skill_content() and _create_resource_element() shared
      helpers from InlineSkill for reuse
    - Add _discover_marked_members() for scanning class hierarchies
    - Add _make_method_name() for Python-to-skill name conversion
    - Add class_based_skill sample (UnitConverterSkill)
    - Update mixed_skills sample with TemperatureConverterSkill
    - Add 58 new tests covering ClassSkill, decorator discovery, property
      resources, inheritance, kwargs forwarding, and duplicate detection
    - Export ClassSkill from agent_framework public API
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: replace try/except/continue with assignment to satisfy bandit B112
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * address PR review feedback
    
    - Walk cls.__mro__ in _discover_marked_members for inherited property resources
    - Use inspect.getattr_static for MRO-aware is_property check
    - Return defensive copies from resources/scripts properties
    - Raise TypeError on wrong decorator stacking order (@resource above @property)
    - Log warning instead of silently swallowing descriptor errors during discovery
    - Validate explicit name= at decoration time via _validate_member_name
    - Add tests for all of the above
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Fix temperature converter skill: make resource necessary for script
    
    Refactor TemperatureConverterSkill so the agent must read the
    formulas resource (factor/offset) before calling the script,
    aligning with the volume-converter pattern.
    
    - Resource: numeric factor/offset table instead of symbolic formulas
    - Script: generic linear transform (value * factor + offset)
    - Instructions: updated to reflect new workflow
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Fix MCPStreamableHTTPTool leaking asyncio.CancelledError when MCP server is unreachable (#5687)
    * fix: wrap asyncio.CancelledError in ToolException in _connect_on_owner (#5667)
    
    asyncio.CancelledError is a BaseException (not Exception) in Python 3.8+.
    When an MCP server is unreachable, the MCP library's internal anyio task
    group raises CancelledError, which escaped all three 'except Exception'
    handlers in _connect_on_owner(). This propagated through
    _run_lifecycle_owner -> _run_on_lifecycle_owner -> connect -> __aenter__,
    bypassing user except Exception blocks entirely.
    
    Fix: change the three except-Exception clauses in _connect_on_owner to
    'except (Exception, asyncio.CancelledError)' so spurious CancelledErrors
    from the MCP transport layer are caught and wrapped in ToolException,
    consistent with the method's documented contract.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(mcp): propagate genuine task CancelledError in connect() (#5667)
    
    On Python >= 3.11, check task.cancelling() > 0 before wrapping
    CancelledError as ToolException in the three except blocks inside
    _connect_on_owner(). When the current task is being cancelled by its
    caller, the CancelledError now propagates after cleanup, consistent
    with the existing pattern at _mcp.py:560-564 and _runner.py:115-120.
    
    On Python < 3.11 task.cancelling() is unavailable, so MCP-internal
    CancelledErrors still cannot be reliably distinguished from
    caller-driven cancellation; they continue to be wrapped as
    ToolException with a comment documenting the trade-off.
    
    Tests:
    - Add cleanup assertion to transport-creation CancelledError test
    - Add MCPStdioTool variants exercising the 'command' message branches
      for both transport-creation and initialize CancelledError paths
    - Add Python 3.11+-gated tests verifying genuine task cancellation
      propagates (and still cleans up) for transport and initialize stages
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(mcp): log CancelledError with exc_info before wrapping in ToolException (#5667)
    
    CancelledError inherits from BaseException (not Exception) on Python >= 3.8,
    so the 'inner_exception=ex if isinstance(ex, Exception) else None' guard
    always yields None for CancelledError. This means ToolException.__init__
    calls logger.log(level, message, exc_info=None), dropping the traceback.
    
    Add an explicit logger.debug(error_msg, exc_info=ex) before each
    raise ToolException(...) in the three CancelledError handlers so the
    full traceback is preserved in debug logs when MCP-internal cancellation
    is wrapped rather than propagated.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review feedback for #5667: Python: [Bug]: Error Handling Issue regarding Python MCPStreamableHTTPTool Class
    
    * refactor(_mcp): extract cancellation helper, fix session error msg and exc_info
    
    - Extract _should_propagate_cancelled_error() helper to eliminate duplicated
      genuine-cancellation detection logic across the three connect() except blocks
    - Fix session-creation ToolException message to include exception details
      (e.g. 'Failed to create MCP session: <ex>') matching the transport and
      initialize failure paths
    - Change exc_info=ex to exc_info=True in all three logger.debug() calls
      for idiomatic logging
    - Add tests for _should_propagate_cancelled_error helper
    - Add regression test asserting session error message includes exception text
    - Add test verifying logger.debug is called with exc_info=True
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor: factor out _close_and_check_cancelled helper in _connect_on_owner
    
    Addresses review comment on PR #5687:
    
    1. Add _close_and_check_cancelled() helper method that combines
       _safe_close_exit_stack() + _should_propagate_cancelled_error() into a
       single await-able call. This eliminates the duplicated close-then-check
       pattern that appeared identically in all three connect phases (transport,
       session, initialize), reducing future drift risk.
    
    2. Comments 2 and 3 (missing {ex} in session error message and non-idiomatic
       exc_info=ex) were already addressed in the current code: all error messages
       include {ex} and all logger.debug calls use exc_info=True.
    
    3. Add test_connect_genuine_cancellation_during_session_creation_propagates
       to cover the previously untested genuine-cancellation path in the
       session-creation phase (transport and initialize phases already had tests).
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review feedback for #5667: review comment fixes
    
    ---------
    
    Co-authored-by: Copilot <copilot@github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Add base_url parameter to AnthropicClient and RawAnthropicClient (#5685)
    * feat(anthropic): add base_url parameter to AnthropicClient and RawAnthropicClient
    
    Add base_url support to AnthropicSettings TypedDict, RawAnthropicClient,
    and AnthropicClient so users can point the client at Foundry or other
    Anthropic-compatible endpoints without having to construct AsyncAnthropic
    manually.
    
    - Add base_url field to AnthropicSettings (resolved from ANTHROPIC_BASE_URL env var)
    - Add base_url parameter to RawAnthropicClient.__init__ and pass it to AsyncAnthropic
    - Add base_url parameter to AnthropicClient.__init__ and forward to super
    - Add unit tests for base_url on both client classes
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: Add `base_url` parameter to `AnthropicClient` and `RawAnthropicClient`
    
    Fixes #5683
    
    * test: add ANTHROPIC_BASE_URL env fallback tests for issue #5683
    
    Add unit tests verifying that both AnthropicClient and RawAnthropicClient
    pick up base_url from the ANTHROPIC_BASE_URL environment variable via
    load_settings when base_url is not passed explicitly as a constructor arg.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * test(anthropic): explicit base_url kwarg beats ANTHROPIC_BASE_URL env var (#5683)
    
    Add regression tests asserting that when both ANTHROPIC_BASE_URL is set
    in the environment *and* an explicit base_url kwarg is passed to
    AnthropicClient / RawAnthropicClient, the explicit kwarg wins.
    
    This closes the priority-ordering contract (explicit arg > env var) that
    the existing tests left implicit.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <copilot@github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Core: notify agent of external AgentModeProvider mode changes (#5650)
    When the operating mode is changed externally (e.g. via a slash-command handler
    calling set_agent_mode), the agent's chat history still shows the prior set_mode
    tool call near the end. Updating only the system instructions is insufficient —
    models tend to anchor on the recent tool call and ignore the new mode.
    
    Mirror the .NET AgentModeProvider behavior: when set_agent_mode detects an actual
    mode change, record the previous mode in provider state. On the next before_run,
    the provider pops that flag and injects a user-role notification message
    announcing the switch, so the most recent context unambiguously reflects the
    current mode. The agent-driven set_mode tool path bypasses this so it does not
    trigger a redundant notification on its own change.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption (#5671)
    * Remove Foundry toolbox helpers; standardize on MCP for toolbox consumption
    
    - Remove RawFoundryChatClient.get_toolbox() and its fetch_toolbox import
    - Remove fetch_toolbox, select_toolbox_tools, get_toolbox_tool_name,
      get_toolbox_tool_type, FoundryHostedToolType, ToolboxToolSelectionInput
      from agent_framework_foundry._tools
    - Remove ExperimentalFeature.TOOLBOXES from _feature_stage.py (no consumers)
    - Drop toolbox re-exports from agent_framework_foundry/__init__.py and
      agent_framework.foundry namespace
    - Update _sanitize_foundry_response_tool docstring to remove toolbox framing;
      sanitization logic itself is unchanged
    - Update _agent.py docstring: 'toolbox-fetched MCP' → 'hosted MCP'
    - Delete tests/test_toolbox.py (all tests covered removed helpers)
    - Update test_foundry_chat_client.py: rename/redoc tests that mentioned
      toolbox but test sanitization that remains
    - Delete foundry_chat_client_with_toolbox.py (bespoke toolbox API sample)
    - Delete foundry_toolbox_context_provider.py (relied on select_toolbox_tools)
    - Rename foundry_chat_client_with_toolbox_mcp.py →
      foundry_chat_client_with_toolbox.py (canonical MCP pattern)
    - Rewrite 04_foundry_toolbox/main.py to use MCPStreamableHTTPTool
    - Update provider/README, context_providers/README, 04_foundry_toolbox/README
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(samples): update 06_files sample to consume toolbox via MCP (#5670)
    
    Replace removed get_toolbox/select_toolbox_tools APIs with
    MCPStreamableHTTPTool, using allowed_tools=["code_interpreter"] to
    select only the code interpreter from the toolbox endpoint.
    
    Update .env.example and README to use FOUNDRY_TOOLBOX_ENDPOINT
    instead of TOOLBOX_NAME.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): remove non-existent toolbox helper APIs from README (#5670)
    
    Remove the 'fetch, optionally filter, and pass tools directly' pattern
    from the FoundryChatClient toolbox documentation, as select_toolbox_tools
    and get_toolbox were removed. Only the MCP endpoint pattern is documented.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(foundry): remove residual toolbox docstring references and reproduction report
    
    Remove REPRODUCTION_REPORT.md (workflow artifact that should not be committed),
    and update two remaining docstring references that still said 'toolbox reads'
    /'toolbox definition' after the toolbox helpers were removed.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption
    
    Fixes #5670
    
    * fix(#5670): resolve toolbox endpoint from TOOLBOX_NAME fallback; add namespace regression tests
    
    - Add _resolve_toolbox_endpoint() helper in 04_foundry_toolbox/main.py and
      06_files/main.py that prefers FOUNDRY_TOOLBOX_ENDPOINT but falls back to
      deriving the MCP URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME — fixing
      the startup KeyError when agents are deployed via azd provision (which injects
      TOOLBOX_NAME, not FOUNDRY_TOOLBOX_ENDPOINT).
    - Update 04_foundry_toolbox/.env.example to use FOUNDRY_TOOLBOX_ENDPOINT
      (consistent with 06_files).
    - Add TOOLBOX_NAME env var to 06_files/agent.yaml so deployed agents have it
      available for the fallback derivation.
    - Update both READMEs to document the two ways to supply the toolbox endpoint.
    - Add test_foundry_namespace_no_longer_exposes_toolbox_helpers() with negative
      assertions for FoundryHostedToolType, get_toolbox_tool_name,
      get_toolbox_tool_type, and select_toolbox_tools — guarding against accidental
      re-introduction of removed symbols.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix(samples): fail fast on empty FOUNDRY_TOOLBOX_ENDPOINT; add unit tests
    
    Addresses review feedback for #5670:
    
    - In _resolve_toolbox_endpoint() (04_foundry_toolbox/main.py and
      06_files/main.py) change the walrus-operator check from a truthy
      test to an explicit 'is not None' guard.  An explicitly set empty
      string now raises ValueError immediately with a clear message
      instead of silently falling through to the fallback URL
      construction.
    
    - Add tests/samples/hosting/test_toolbox_endpoint.py covering both
      sample modules:
        (a) FOUNDRY_TOOLBOX_ENDPOINT set → returned as-is
        (b) FOUNDRY_TOOLBOX_ENDPOINT set to empty string → ValueError
        (c) fallback constructs URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME,
            stripping trailing slashes
        (d) neither variable group set → KeyError
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address review feedback: remove extraneous test and docstring content
    
    - Remove test_foundry_namespace_no_longer_exposes_toolbox_helpers (no longer warranted)
    - Remove docstring from _agent.py _prepare_tools_for_openai (extraneous)
    - Trim _chat_client.py _prepare_tools_for_openai docstring to one-liner (toolbox references no longer relevant)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: remove remaining extraneous docstring from RawFoundryChatClient._prepare_tools_for_openai
    
    Address review comment on PR #5671: reviewer noted the description
    isn't warranted now that toolbox helpers have been removed. Matches
    the pattern in RawFoundryAgentChatClient which has no docstring.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <copilot@github.com>
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
  • Python: [Breaking] Restructure agent skills to use multi-source architecture (#5584)
    * migrate skills to multi source architecture
    
    * Fix ruff lint errors in skills module (ASYNC240, SIM108, E501)
    
    - Use anyio.Path for async file I/O in _FileSkillResource.read()
    - Use noqa: ASYNC240 for pure string os.path calls in async context
    - Restore pre-commit if/else pattern in InlineSkillScript.run()
    - Break long lines to fit 120-char limit in _skills.py and test_skills.py
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: collapse multi-line lambdas to single lines to fix pyright errors
    
    The pyright ignore comments only suppress errors on the same line, so
    multi-line lambdas left arguments on continuation lines uncovered.
    Collapse both lambdas to single lines matching the existing load_skill
    lambda pattern.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: replace untyped lambdas with typed inner functions to fix pyright errors
    
    Python lambdas cannot have type annotations, so pyright reports
    reportUnknownLambdaType and reportUnknownArgumentType errors that
    cannot be suppressed with inline ignore comments. Replace the
    lambdas for read_skill_resource and run_skill_script with typed
    inner async functions.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: address PR review feedback on docs and prompt template
    
    - Update with_prompt_template() docstring to document the
      {resource_instructions} placeholder requirement
    - Remove stray backslashes after {resource_instructions} and
      {runner_instructions} in DEFAULT_SKILLS_INSTRUCTION_PROMPT
    - Update subprocess_script_runner docstring to reflect
      FileSkillScript.full_path usage
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor: replace dict[str, Skill] with Sequence[Skill] in SkillsProvider
    
    Replace internal dict-based skills storage with Sequence[Skill] to
    eliminate silent duplicate overwrites and simplify the code. Add
    _find_skill helper for case-insensitive linear lookup.
    
    Also fix pyright errors in tests by adding isinstance assertions
    before accessing .function on SkillResource/SkillScript base types.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor: add read-time resource path validation in _FileSkillsSource
    
    Move security validation (path-traversal and symlink guards) for
    file-based skill resources into _FileSkillsSource, restoring the
    read-time checks that existed in main via _read_file_skill_resource.
    
    - Add _get_validated_resource_path static method on _FileSkillsSource
      that validates containment, existence, and symlink safety
    - _FileSkillsSource.get_skills() validates resource paths at discovery
      time via _get_validated_resource_path before passing to _FileSkillResource
    - Move _normalize_resource_path, _is_path_within_directory, and
      _has_symlink_in_path from module-level into _FileSkillsSource as
      static methods (only used there)
    - _FileSkillResource remains a simple path-to-content reader
    - Add tests for _get_validated_resource_path security checks
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * fix: reject str/Path in SkillsProvider constructor to prevent str-as-Sequence ambiguity
    
    Since str is a Sequence, passing a path string to the source parameter
    would silently be treated as a sequence of characters instead of a
    file source. Add an explicit TypeError with a helpful message pointing
    callers to SkillsProvider.from_paths().
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * Address PR #5584 review feedback
    
    - Remove .NET reference from _FileSkillResource docstring
    - Fix inconsistent resource name example (references/FAQ.md -> references/FAQ)
    - Simplify SkillsProvider usage in code_defined_skill sample (pass single skill directly)
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * remove skillsproviderbuilder
    
    * Update python/packages/core/agent_framework/_skills.py
    
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
    
    * fix: remove dead code and fix sync function call in InlineSkillResource.read()
    
    - Change await self.function() to self.function() for sync functions
      without **kwargs; async results are handled by inspect.isawaitable()
    - Remove unreachable raise ValueError since __init__ already validates
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * remove full_path unnecessary property
    
    * replace anyio with asyncio.to_thread for file I/O in _FileSkillResource
    
    Replace anyio.Path usage with asyncio.to_thread + pathlib.Path since
    anyio is not a direct dependency of core (transitive via mcp).
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * simplify awaitable check to return directly
    
    Use 'return await result' instead of assigning then returning.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * address PR review feedback for skills refactoring
    
    - Replace anyio with asyncio.to_thread + pathlib.Path for file I/O
    - Simplify awaitable check to return directly
    - Remove unnecessary function None guard in InlineSkillResource.read()
    - Add assert for type narrowing on self.function
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * address PR review feedback for skills refactoring
    
    - Replace anyio with asyncio.to_thread + pathlib.Path for file I/O
    - Simplify awaitable checks to return directly
    - Remove unnecessary function None guard in InlineSkillResource.read()
    - Use typing.cast instead of assert for type narrowing
    - Add caching behavior note to SkillsProvider docstring
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    * refactor: move name/description from abstract properties to Skill.__init__
    
    Replace abstract properties for name and description on the Skill ABC
    with a base __init__ that validates and stores them as regular
    attributes. This simplifies custom Skill subclasses (only content
    remains abstract) and centralizes validation in the base class,
    consistent with SkillResource and SkillScript base classes.
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    
    ---------
    
    Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
    Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>